Government Bonds in Domestic and Foreign Currency: The Role of Institutional and Macroeconomic Factors *

Stijn Claessens Daniela Klingebiel

Sergio L. Schmukler

REVIEW OF INTERNATIONAL ECONOMICS Forthcoming

Abstract In contrast to some recent research, this paper finds that institutional and macroeconomic factors are related to the depth and currency composition of government bond markets. Using panel data for developed and emerging economies, we find several factors to be systematically associated with bond markets. Aside from economic size (already shown to affect the currency composition), this paper shows that investor bases matter. Economies with deeper domestic financial systems (measured by bank deposits and stock market capitalization) have larger domestic currency bond markets and issue less foreign currency debt, whereas foreign investor demand is positively related to the size and share of foreign currency bonds. Moreover, less flexible exchange rate regimes are associated with more foreign currency issuance. Other relevant variables include inflation, fiscal burden, legal origin, and capital account openness. JEL Classification Numbers: F21, F33, F34, F36, G15, G18 Keywords: government debt, government bond markets, sovereign bonds, foreign currency debt, currency structure Contact Author: Sergio L. Schmukler, The World Bank, MSN MC3-301, 1818 H Street, NW, Washington, DC, 20433, Tel.: (202) 458-4167, Fax: (202) 522-3518, Email: sschmukler@worldbank.org

* Claessens: University of Amsterdam, CEPR, World Bank, 1818 H Street, NW, Washington, DC, 20433 Klingebiel and Schmukler: World Bank, 1818 H Street, NW, Washington, DC, 20433 For very useful comments, we thank Mark Aguiar, Menzie Chinn, Olivier Jeanne, Ricardo Hausmann, Eduardo Levy Yeyati, Ron McKinnon, Ugo Panizza, Frank Warnock, Dariusz Wojcik, two anonymous referees, and participants at presentations held at Stanford University, the Kiel Institute of World Economics, and the AEA Meetings (San Diego). We are also grateful to Juan Carlos Gozzi and Guillermo Noguera for outstanding research assistance and to Denis Petre from the BIS for the data. This paper was revised while Schmukler was visiting the IMF.

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1. Introduction

During the last two decades, capital markets around the world have experienced rapid

growth and have become increasingly more integrated. These trends are reflected in the

growth of domestic public bond markets and the government participation in

international capital markets. At the same time, there have been many financial crises,

especially in emerging markets, a phenomenon that has been partly attributed to the

increase in debt burdens, particularly in foreign currency. These factors have led to a

growing interest regarding the determinants of government bond market development and

the currency composition of government bonds.

The literature that studies government debt markets is large, but the particular

attention on government bonds emerged in the last decade, as governments replaced bank

borrowing with bond issuance. Studies on the general determinants of governments’

desire and ability to issue debt have highlighted macroeconomic stability and political

economy factors.1 The literature following the debt crisis of the early 1980s has

concentrated on a country’s ability to issue external debt, then mostly in the form of

commercial bank loans.2 Following the Brady plan, which resolved the 1980s debt crisis

by converting government debt into bonds, and as new debt took increasingly the form of

international bonds, research evolved into the explanation of spreads and pricing of

government bonds.3 With the financial crises in the 1990s, government bonds gained

even more interest as the size and structure (currency and maturity) of government debt

has been identified to lead to vulnerabilities, mismatches, and possibly trigger financial

crises.4

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The currency composition of government bonds has especially received much

attention lately, with a number of dimensions being considered. For some countries,

particularly emerging economies, borrowing in foreign currency can be less expensive

than in domestic currency (or at least appear to be so). But foreign currency debt exposes

governments and firms to exchange rate risk, as their revenues typically relate to local

currency values. This mismatch increases the likelihood of financial crises and may

make self-fulfilling runs possible (see, for example, Krugman, 1999; Jeanne, 2000;

Aghion, Bacchetta, and Banerjee, 2001; and Schneider and Tornell, 2004).

A recent empirical literature analyzes specifically the currency composition of

debt and highlights the phenomenon of “original sin,” defined as the inability of

emerging economies to borrow abroad in their domestic currency (even short term) and

to borrow long term in domestic currency in the local market (Eichengreen and

Hausmann, 1999; Hausmann, Panizza, and Stein, 2001; Eichengreen, Hausmann, and

Panizza, 2002; Hausmann and Panizza, 2003; and Chamon and Hausmann, 2005). This

literature generally finds that a small number of institutional and macroeconomic factors

explain the ability of countries to issue in domestic currency. Eichengreen, Hausmann,

and Panizza (2002) and Hausmann and Panizza (2003) specifically find that only country

size matters for explaining their measures of “international original sin,” i.e. the currency

composition of government debt issued in foreign markets. Though they also find that

some institutional factors affect the ability of governments to issue domestic currency

denominated debt in the local market (“domestic original sin”), given the few degrees of

freedom and lack of consistency, they give little value to these results. In a different

paper, Jeanne (2005) argues that monetary credibility matters for liability dollarization.

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In another paper, Burger and Warnock (2004) conduct a study of how foreign investors

participate in private and public domestic currency bond markets. They find that some

institutional factors, specifically more creditor-friendly policies and laws, help in the

development of domestic currency markets. In their study, they also analyze whether

domestic currency bonds are attractive to U.S. investors and estimate a CAPM model to

see how much U.S. investors value diversifiable idiosyncratic risk.5

While the original sin literature downplays the importance of specific

macroeconomic and institutional factors and argues that it is difficult to pinpoint the

exact causes behind the inability of governments to issue domestic currency bonds, this

literature highlights the role of international factors and path dependence in foreign

exchange borrowing. In the presence of international transaction costs, investors have

limited incentives to hold currencies issued by small countries, since these countries offer

limited diversification benefits relative to the transaction costs (Hausmann and Rigobon,

2003). This implies that larger countries have an advantage when issuing debt in local

currency, consistent with the conclusion from the original sin literature that only the size

of the economy matters for the currency composition of international debt. Additionally,

this literature also emphasizes that historical factors have played a significant role in

helping countries overcome the original sin and that network externalities have given rise

to path dependence, since a currency used in some international transactions becomes

more advantageous for additional traders and investors to use.6 This path dependence

and the evidence from the original sin literature imply that there are few policy options

available to many emerging countries needing to raise financing, as policymakers cannot

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alter initial conditions and improvements in policies and institutions do not seem to affect

their ability to issue domestic currency debt.7

In this paper we reconsider the evidence presented by the original sin literature

and ask: Are institutional and macroeconomic factors, aside from size, indeed unrelated

to the development of bond markets, in particular the currency structure? To analyze this

question, we study systematically whether institutional and macroeconomic factors affect

the level of both domestic and foreign currency government bonds relative to GDP, as

well as the share of foreign currency bonds in total bonds.8 Our data cover both short-

and long-term debt securities, including bonds, notes, treasury bills, and other short-term

instruments issued by the government in the money market. This seems relevant because

using data of a certain maturity would tilt the currency composition, as many countries

tend to issue long-term bonds in foreign currency and short-term bonds in domestic one.9

To conduct the analysis, we use a relatively long time period, 1993-2000, covering both

developed and developing countries. Early in this period, many government bond

markets were established and rapidly developed thereafter. The wide country coverage

allows us to identify better some of the factors that lead and enable governments to issue

bonds.

We depart from the original sin literature in various dimensions. With respect to

the variables under study, there are two differences. First, we analyze the determinants of

not only the currency composition but also the depth of government bond markets.

Understanding the determinants of the size of bond markets is important because their

depth has been related to both financial development and financial crises.10 Second, we

focus on the currency denomination of government bonds, without distinguishing the

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place of issuance. In a world of increasing financial integration, domestic investors can

purchase domestic bonds in international markets, while foreign investors can also buy

domestic bonds in domestic markets. So, aside from the legal and regulatory

considerations discussed elsewhere, we believe that the distinction between the places of

issuance is not that informative. With respect to the sample under study, we concentrate

on a sample of countries for which the Bank for International Settlements (BIS) collected

data, and which have actively issued bonds during the 1990s. With respect to the

explanatory variables, we analyze a wide range of macroeconomic and institutional

factors, many of them not analyzed before in the context of government bonds.

We find that economies that are bigger and have greater domestic investor bases,

as proxied by the size of their financial systems, have relatively larger domestic bond

markets and issue relatively less foreign currency debt. On the contrary, foreign investor

demand (measured alternatively by the government bonds and notes held by non-

residents over GDP, holdings of a country’s long-term debt securities by U.S. investors,

and total debt securities held by foreign investors) is positively associated with foreign

currency bond issuance, both as a share of GDP and total government bonds

outstanding.11 Important for the recent debate on limiting financial crises, we find that

less flexible exchange rate regimes are associated with more foreign currency issuance.

Other relevant variables for the size and composition of bond markets include inflation,

fiscal burden, legal origin, and capital account openness. These results differ from those

obtained by the original sin literature. We conclude, therefore, that it is difficult to

neglect institutional and macroeconomic factors when trying to understand the

development of government bond markets in domestic and foreign currency.

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The rest of the paper is organized as follows. Section 2 describes the data and

presents some descriptive statistics on bond markets. Section 3 discusses the empirical

strategy to study the factors affecting the size and structure of government bond markets.

Section 4 shows the estimation results. Section 5 discusses the results from various

robustness tests and alternative specifications. Section 6 concludes.

2. Data on Government Bonds

We are interested in explaining the size of government bond markets in domestic and

foreign currency across countries, as well as the share of public bonds denominated in

foreign exchange. We also want to cover the largest sample of countries and the longest

time period available, comprising both domestic and international issuance, and detailing

the currency choices. Data sources and availability differ, however, depending on the

issuing country (particularly, developed versus emerging economies) and the issuing

market (domestic versus international markets). While there is a fairly comprehensive

coverage for domestic and international markets for many developed countries (though

even here good coverage is quite recent), reliable and complete data are still scarce for

many emerging market economies. Moreover, in many cases, a particular source of data

covers only one market.

Reviewing the various sources available, the Bank for International Settlements

(BIS) appears to be the most comprehensive one in terms of countries, years, markets,

and types of securities covered. The BIS collects security-level data from the Bank of

England, Capital Data, Euroclear, International Securities Market Association (ISMA),

and various national sources, mostly central banks. The BIS publishes these data on an

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aggregate basis, addressing, among others, the problem of double counting. For domestic

markets, that is, bonds issued domestically, the BIS covers the public sectors of some 41

countries from 1989 to the present on a quarterly basis, comprising amounts outstanding

as well as net new issues. For international markets, the BIS provides quarterly data for

77 countries, but the coverage starts only in the third quarter of 1993.12 All data are

measured in current U.S. dollars.

We want to understand the size of government bond markets in both domestic and

foreign currency. While the BIS data include information on the currency composition of

the amount outstanding of all government bonds, we are, however, not interested in the

detailed structure of bonds across different non-local currencies.13 So we use the BIS

information on currency composition to classify bonds into two categories: local currency

denominated issues versus foreign currency denominated issues. Foreign currency bonds

aggregate all amounts outstanding in currencies other than the local currency. This

classification is irrespective of the place of issuance. Note that we use data obtained from

the BIS, which are unavailable in its website, as the BIS does not publish data on the

currency composition of the bonds issued by each country (it only reports aggregate data

on the currency composition). Our data are equivalent to the sum of long-term (bonds

and notes) and short-term (money market instruments) securities reported in the BIS

website.

To cross check the data, we collected independent information from finance

ministries and central banks of various countries (including those of Argentina, Brazil,

France, Mexico, the Netherlands, Poland, Sweden, and Turkey). In the case of

Argentina, we decided to use government sources instead of the BIS data because the

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domestic currency bonds from the BIS include foreign currency bonds issued

domestically, which constitute a significant amount for this country. For the other

countries we verified, the BIS information and the government information coincided, so

we continued to use the BIS data.

Based on the compiled data, we construct year-end values of the amounts

outstanding of government bonds in local and foreign currency and the year-end foreign

currency share. We use year-end data, as our explanatory variables are generally

available only on an annual basis. The final dataset of those countries and years for

which we have the amounts outstanding in both domestic and international markets, as

well as the currency breakdown, has a reduced coverage; it comprises data for 35

countries between 1993 and 2000.

Next, we provide some descriptive statistics of the bond data compiled. The

overall size of the global government bond market is shown in Figure 1. In absolute

(nominal) U.S. dollars terms, government bond markets in developed and emerging

economies expanded from 13.1 trillion in 1993 to 19.1 trillion in 2000. In relative terms,

government bond markets of emerging economies increased more, from 317 billion in

1993 to 1.1 trillion in 2000. Despite the large percentage increase, emerging markets still

represented less than six percent of the world government bond market in 2000.14

The share of foreign currency denominated bonds over total bonds is displayed in

Figure 2. The chart shows that emerging market economies are increasingly issuing

government bonds in currencies other than their own, from a mean share of 9.2 percent in

1993 to 26.8 percent in 1998, with a decline to 22.8 percent in 2000. On the contrary,

developed countries show a declining trend in the share of foreign currency bonds, from

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21.8 percent to 15.5 percent over the same period. Though not reported, there are

differences across countries. A large increase in foreign currency borrowing takes place

for Latin American countries, from a mean of 4.3 percent in 1993 to 46.9 percent in 1996,

declining somewhat to 35.6 percent in 2000, with a high in 2000 of 95.3 percent for

Argentina. In Europe, transition economies also start to issue relatively more debt in

foreign currency towards the end of the decade. The share of foreign currency bonds is

the lowest for Germany and the U.S.15

The differences between developed countries and emerging markets in terms of

absolute amounts and debt composition (that is, the share of foreign currency issues)

become even clearer when analyzing in more detail the structure of the global

government bond market in 2000. Figure 3 shows that of the 19.1 trillion U.S. dollars in

government debt outstanding among the 35 countries covered in our sample, 95 percent is

on account of developed countries. The figure also shows that foreign currency issues

are much more important for emerging market governments than for developed country

governments, 20 percent of total bonds outstanding versus two percent in 2000.

Figure 4 shows the ratio of government bond stocks relative to countries’ gross

domestic product (GDP).16 Countries with higher debt ratios are mostly developed

countries. This may be because these countries have stronger repayment capacity and

can sustain higher debt-to-GDP ratios.17 Figure 5 shows the share of foreign currency

claims. The figure shows the importance of foreign exchange bonds for countries like

Argentina, Iceland, Russia, and Sweden, as well as for some special cases like

Luxembourg, which is a major financial center for the issuance and trading of

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Eurobonds.18 The figure also confirms that developed countries tend to issue more debt

in their own currency, although there are exceptions.

3. Empirical Methodology

We now turn to the empirical analysis of the determinants of the size and currency

composition of government bond markets. The variables we want to explain are the ratio

of local currency government bonds and the ratio of foreign currency bonds to GDP,

while the currency choice variable is the ratio of foreign currency government bonds to

total government bonds. The dependent variables are in logs. In the basic results, we

estimate the relation between these three variables and a set of regressors using panel

feasible generalized least squared (FGLS) estimations, allowing for heteroskedastic error

structures and different autocorrelation coefficients within countries. We next specify the

set of explanatory variables we use in our basic results.

We want to understand whether institutional and macroeconomic characteristics

and policies affect the size and currency structure of government bonds. The literature

suggests a long list of variables to use as controls in our regressions. For our first

selection, we are mostly guided by the more recent literature. The first set of results is

reported in Table 1. In subsequent tables, we do extensive robustness tests and

investigate many other variables, as explained in Section 5. The specific explanatory

variables included in the first set of regressions (whose definitions and sources are

detailed in Appendix Table 3) are described next.

First, we control for size. To do so, we use total GDP in nominal U.S. dollars as a

proxy for the size of the economy and the potential scope for developing a (liquid) local

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government bond market. Second, we control for domestic financial development by

using the ratio of the total deposit base in the banking system over nominal GDP, which

is highly correlated with the overall development of the financial system (as shown in

Beck, Demirguc-Kunt, and Levine, 2001). This measure proxies both for the overall

development of the domestic financial system and for the potential domestic demand for

government securities. Though more direct measures of demand would be desirable, we

were unable to find them.19 This lack of good measures of demand calls for caution

when interpreting the impact of this variable. Third, we control for the overall

institutional framework by using a measure called “institutionalized democracy,” which

is part of the Polity IV political economy database maintained at the University of

Maryland. This variable measures the quality of a country’s democratic institutions

imposing constraints on the executive (as well as the degree to which civil liberties are

being guaranteed). This proxy for the political environment addresses the arguments in

the public finance literature that the nature of the political regime and political instability

may have an important effect on the size and scope of government activities, including

government debt. Fourth, we control for two indexes that capture important

macroeconomic factors, believed to be related to government debt issuance. One is an

“inflation policy” index, a subcomponent of the index of economic freedom of the

Heritage Foundation. The index represents the absence of strict monetary policy and is

based on the average inflation rate over the last ten years, with higher values representing

worse monetary policy. The second index is the “fiscal burden of government,” also a

subcomponent of the index of economic freedom. This variable measures the fiscal

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pressure imposed by the government according to the level of a country’s corporate tax

rates and the overall size of government expenditure.

Finally, the last set of variables relates to the exchange rate regime and analyzes

the link between the flexibility of the exchange regime and the size of the domestic and

foreign currency debt markets. We use, alternatively, one of three indexes of exchange

rate regimes. One index reflects the officially announced or “de jure” exchange rate

regime. But, since countries often do not follow the regime they publicly announce, we

use two other indexes that depict the actual or “de facto” exchange rate regime, one

developed by Reinhart and Rogoff (RR) (2004) and another by Levy Yeyati and

Sturzenegger (LYS) (2003). The use of alternative indexes is important because the

correlation among them is not very high, as reported in Frankel (2004).

The inclusion of the exchange rate regime variable is important because it has

already been associated to the currency denomination of debt. Two views exist in this

respect. Proponents of hard (fixed) currency pegs argue that a strong domestic currency

can provide credibility and lead to greater domestic currency financial intermediation,

thereby allowing countries to issue more local currency debt over time.20 But others

argue that a fixed exchange rate increases the short-run incentives of both the government

and the private sector to issue debt in foreign currency, adding to the degree of “liability

dollarization.” Governments with more fixed regimes may want to signal the credibility

of their regime by issuing relatively more foreign currency debt. As foreign currency

debt tends to be cheaper (at least in contractual terms), it is difficult to justify issuing

domestic currency debt instead of less expensive foreign currency debt and, at the same

time, claim that the supposedly rigid regime will persist over time. This was very clear in

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the case of Argentina, where the degree of debt dollarization increased steadily over time,

since the inception of its currency board in 1991 (de la Torre, Levy Yeyati, and

Schmukler, 2003). For the private sector, fixed exchange rate regimes might induce

agents to underestimate the possibility of future currency changes, leading to excessive

foreign exchange borrowing (Eichengreen, 1994), and might also induce moral hazard in

the presence of implicit or explicit government bailout guarantees (McKinnon and Pill,

1998; Dooley, 2000; Burnside, Eichenbaum, and Rebelo, 2001; and Schneider and

Tornell, 2004). The exchange rate regime might also affect the currency composition of

debt by modifying the relative return volatilities of domestic and foreign currency assets.

Ize and Levy Yeyati (2003) show that, in a minimum variance portfolio equilibrium,

financial dollarization is explained by the relative volatilities of inflation and the real

exchange rate. In this context, policies that limit exchange rate volatility, such as

following a crawling peg or using monetary policy to target the nominal exchange rate,

increase dollarization.

Many variables suggested by the literature can be subject to the criticism of being

endogenous. In our particular case, contemporaneous values of inflation, fiscal burden,

and the exchange rate regime can be vulnerable to this criticism. For example, countries

with larger debt may be able to avoid using inflation as a means to raise revenues and

finance higher expenditure levels, leading to lower scores on the inflation and fiscal

burden indexes. But what could be more problematic is the potential endogeneity of the

exchange rate regime. In other words, the degree of foreign currency liabilities can affect

whether countries choose to let their currencies float. This potential endogeneity of the

exchange rate regime has led to the literature on “fear of floating” (Calvo and Reinhart,

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2002). Also, Devereux and Lane (2003) highlight its potential endogeneity to the

structure of a country’s liabilities. To try to avoid endogeneity from affecting our results,

we use as much as possible institutional variables and macroeconomic indexes, which

should be less sensitive to the evolution of bond markets themselves. Moreover, we use

lagged and, alternatively, initial values of the potentially problematic variables, since it is

difficult to find good instruments and we expect those lagged and initial values to be less

affected by endogeneity concerns. Section 5 further addresses this issue by reporting two

additional estimates that try to deal with the potential endogeneity, describing the

difficulties in finding good alternative instruments, and discussing and illustrating the

possible causality patterns in the data with respect to the exchange rate regime.

4. Regression Results

The first set of econometric results are presented in Table 1, with each panel of the table

displaying regression results for one dependent variable at a time – the log of local

currency denominated bonds over GDP, the log of foreign currency denominated bonds

over GDP, and the log of the share of foreign currency bonds – and using in every panel

the same set of independent variables. The different columns display several

specifications, depending on which exchange rate regime variable is used, and whether

lagged or initial values of the potentially endogenous variables are used. The number of

observations varies slightly, given that the exchange rate regime variables have different

country and time coverage. Wald tests (not reported) show that the explanatory variables

are always jointly significant.

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The top panel with the log of local currency bonds over GDP as the dependent

variable shows that countries with bigger economies have relatively larger local currency

government bond markets. This result is very robust and holds across specifications.

This suggests that scale effects exist in the development of local government bond

markets. These economies of scale may exist in the development of the infrastructure of

local bond markets, including incurring the fixed costs of establishing clearing and

settlement systems and developing the legal framework for issuing and trading. Also, it

is very likely that scale effects exist in the liquidity of secondary markets for bonds.21

Regarding the development of the financial system, as proxied by the relative size

of the banking system, we find that countries with more developed systems have more

developed bond markets. This result is very robust and holds across all specifications.

This result may indicate that countries with a more developed financial system have more

demand for government bonds. The specific significance of the banking deposit variable

might reflect the fact that deposit-taking banks directly invest in government paper as

well as that a more developed banking system is associated with a larger institutional

investor base. In addition, a more developed banking system may create demand for

government securities among the general public through better developed distribution

channels, possibly including the presence of a primary dealers network, which may

indirectly increase investors’ interest in buying bonds, also because of more liquid

secondary markets. Of course, a more developed financial system is also often

characterized by a more developed bond market, so it need not be a greater demand that

explains the positive coefficient.

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We now turn to the other institutional and macroeconomic indicators. A robust

result across almost all specifications is the sign of the institutional development variable.

Specifically, countries with good, more democratic institutions have larger government

bond markets relative to their GDP. This suggests that good institutions and democracy

are important in the eyes of investors, maybe as they are associated with a greater

credibility of the state, better quality of decision making, and an easier acceptance by the

public of policies, including macroeconomic policies. This finding confirms evidence

from Isham, Kaufmann, and Pritchett (1995), Acemoglu, Johnson, and Robinson (2000),

and many others regarding the role of institutions in determining the quality of (macro)

economic management. In a narrower sense, that is, for the development of bond

markets specifically, it may be that more effective constraints on a country’s executive

reduce the (perceived) risks of default on government debt, including debt dilution

through inflation spikes. A supply-related explanation can be that more democratic

countries “desire” (and can sustain) a greater role of the government in their economies,

including providing different forms of social insurance (such as unemployment and

pension benefits), leading to higher fiscal expenditures as well as larger debt.

In terms of monetary policies, we find that lower inflation rates are associated

with larger local currency government bond markets. This is to be expected since lower

inflation rates tend to be associated with lower volatilities of inflation and, consequently,

a lower tendency for governments to inflate away the outstanding debt, thus making local

currency debt less risky.22 Another interpretation of this result is that governments with

high inflation do not need to issue large amounts of debt, as the inflation tax is a major

source of government revenue. Regarding fiscal policies, we find that larger government

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expenditure helps sustain larger bond markets. A general larger role of the government,

including presumably the ability of the government to tax the economy more (easily) may

thus affect the willingness of investors to finance the government as well as affect the

desire of governments to issue debt. The significance of the larger fiscal expenditure

could also reflect an underlying desire of citizens for a larger distributive role of the

government, both within a given period through larger expenditures, and between

generations and over time through larger deficits and higher debt stocks. Still, this result

has to be interpreted with some caution since the variable becomes insignificant when

using initial values (columns 5 and 6).

Finally, the three exchange rate regimes variables are mostly significant and have

a positive sign. In other words, countries with a more flexible exchange rate regime (de

jure or de facto) tend to have larger local currency bond markets. On the demand side,

investors in bonds of countries with more flexible exchange rate regimes might be less

fearful of sharp currency depreciations and of large inflation spikes that can decrease the

real value of their investments. And on the supply side, governments with more flexible

exchange rates might finance themselves more through local currency bonds as they have

less desire to signal a commitment to a foreign exchange regime by issuing foreign

currency bonds.

The middle panel presents the results for the log of foreign currency bonds over

GDP. Contrary to the case of domestic currency bonds, the log of GDP variable has a

negative and statistically significant coefficient in all specifications. This result

reinforces the scale effect described above, in the sense that having a smaller domestic

economy may make it more attractive for governments to issue in foreign currency to

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meet their financing needs. This result is in line with the pattern of Figure 2, where

smaller, mostly emerging economies tend to issue more debt in foreign currency. The

coefficient on total deposits to GDP is negative in these regressions, that is, a relatively

better developed financial system decreases the amount of debt issued in foreign

currency, the opposite sign from the regression results for the local currency bond

variable. The variable is also significant in all specifications.

The other institutional and macroeconomic variables are also related to the size of

foreign currency bond markets. However, in contrast to the size of the economy and

financial system development variables, these factors tend to affect foreign currency

bonds in the same direction that they affect domestic currency bonds. Countries with

good democratic institutions have larger foreign currency bond markets, suggesting that

investors are more willing to buy bonds when governments are more legitimate and

policies more credible. Although not always statistically significant, higher inflation is

associated with a smaller stock of foreign currency bonds relative to GDP. In some

sense, this result may be surprising because inflation can be expected to primarily affect

the amount of local currency bonds. But, high inflation is also typically associated with

macroeconomic instability and occasionally with general government defaults, what

might explain the lower demand among investors for both domestic and foreign currency

bonds. Also, as before, when significant, the fiscal burden variable is positively

correlated with foreign currency bonds. The negative signs for the variables that capture

the actual exchange rate regime suggest that countries with de-facto less flexible

exchange rate regimes have larger foreign currency bond markets relative to GDP. This

19

result is consistent with some of the predictions discussed above, in the sense that

exchange rate rigidity prompts governments to issue more debt in foreign currency.

The bottom panel presents the results for the variable foreign currency bonds over

total bonds, i.e., the share of foreign exchange borrowings. To some degree, these results

can already be inferred from the two previous panels, especially when the explanatory

variables have different signs. But the results of this panel show explicitly how the

different variables affect the share of foreign currency bonds. The panel shows that the

absolute size of countries’ GDP and the ratio of deposits to GDP have a negative effect

on the share of foreign currency bonds, i.e., countries with larger economies and

relatively more developed financial systems have a higher share of domestic currency

debt.

The variable institutionalized democracy is statistically significant and positive in

all specifications, suggesting that investors in foreign currency bonds value more than

investors in domestic currency bonds the fact that governments are legitimate and

policies more credible. A higher inflation index is associated with a lower share of

foreign currency debt. The coefficient on the fiscal burden variable is positive, implying

that countries with a higher fiscal burden can or want to issue a higher proportion of

foreign currency debt. Though the official exchange rate regime is positively associated

with the share of foreign currency debt, the two indicators for the actual exchange rate

regime, the more meaningful variables, are negatively and statistically significant

associated with the share. In other words, governments from countries that de facto

follow a more fixed exchange rate regime tend to have a higher proportion of foreign

currency debt, as various papers predict. The differences between using de jure and de

20

facto classifications of exchange rate regimes highlight the disparity between these

classifications and suggest that it is important to analyze the effects of de facto measures.

5. Alternative Specifications

In this section, we discuss the results of estimating a number of alternative specifications.

We conduct these estimations to test the significance of other, previously omitted,

variables and to test whether our results are robust to changes in the regressors and

estimation techniques. Since we estimated a very large number of alternative

specifications, we are unable to report all of them in the paper. We chose to report a set

of estimations that we consider particularly interesting. We comment on the other results

we obtained at the end of this section; those results are available upon request. The

bottom line from this exercise is that institutional and macroeconomic factors are still

important in explaining the size and currency composition of government bond markets,

even when varying considerably the basic framework presented in Section 4. We turn to

the description of the results next.

In the first round of alternative estimates, we focus on the variables related to the

domestic and foreign investor bases. Regarding the domestic side, we consider whether

the specific proxy used for the country’s financial sector development affects our results.

Thus, in addition to the banking system variable (total deposits over GDP), we also

include in the regressions the ratio of stock market capitalization to GDP (in logs).

Regarding the foreign side, we use three variables that measure holdings of debt

securities by foreign investors to proxy for their demand of a country’s bonds. The first

one is the government bonds and notes held by non-residents over GDP. These data

21

come from the International Investment Position (IIP) statistics published by the IMF in

its Balance of Payments Statistics (BOPS). This variable is available for 24 of the

countries in our sample. As a second variable, we use the holdings of a country’s long-

term debt securities by U.S. investors. This variable comes from a comprehensive

benchmark survey of U.S. investment abroad as of December 1997, conducted by the

U.S. Treasury Department and the Board of Governors of the Federal Reserve

System.23,24 Similar data are used by Burger and Warnock (2004) to analyze foreign

investor participation in domestic bond markets. Third, we also use data on long-term

debt securities held by foreign investors, as reported in the IMF Coordinated Portfolio

Investment Survey (CPIS) for 1997 (IMF, 2000).25 For each country, the CPIS reports

data on foreign portfolio asset holdings by residence of issuer. To calculate the holdings

by foreigners of a country’s securities, the holdings of investors in each of the 29

reporting countries are added.26 Similar data are used by Lane (2005) to analyze the

bilateral composition of international bond portfolios in the euro area.27 In a previous

version of the paper, we also used the variable log of international claims over GDP as an

additional independent variable, yielding similar conclusions.28 Table 2 displays the

results with these two new sets of independent variables for all the three dependent

variables; results are shown with lagged values of the independent variables, but using

initial values leads to similar conclusions.

The variable stock market capitalization has a positive coefficient in the

regressions that use local currency bonds over GDP as dependent variable (just as the

total deposits variable does), suggesting that the specific measure for financial sector

development does not drive our results. Furthermore, the total deposits variable remains

22

significant and positive, suggesting that the development of both the banking system and

the stock market are related to domestic currency bond market development. For the

regressions that use foreign currency bonds over GDP as dependent variable, the stock

market capitalization variable is not significant, whereas for the ratio of foreign currency

to total bonds the coefficient is significant and negative in one regression. Again, the

deposit variable keeps its sign and remains statistically significant for all dependent

variables.

The different variables that capture foreign investor demand have all the same

sign; that is, the conclusions remain unaltered across specifications. The results indicate

that as foreign investor demand increases the amount outstanding of both local and

foreign currency bonds over GDP also rises. Interestingly, the effect on foreign currency

bonds is much stronger. Thus, the ratio of foreign currency bonds over total bonds rises

with foreign investor demand. Interestingly, these effects are different than the ones

displayed by the domestic financial system development variables (banking system

deposits and stock market capitalization over GDP), suggesting that domestic investors

tend to purchase bonds in domestic currency, while international investors demand more

bonds in foreign currency. While this supports much casual observation, it goes against

the portfolio allocation models that imply that investors should spread their investment

over various currencies. As such, these relations may be due to a form of home bias in

that investors prefer instruments denominated in their own currency.

Second, we investigate whether our choice of institutional variables affects the

results. We explore specifically whether controlling for the general degree of

development, the origin of the country’s legal system, and the degree of capital account

23

openness affects our previous results. We also study the significance of these variables.

One can expect that more developed countries have better institutions and, consequently,

have more developed bond markets. Furthermore, GDP per capita is the broadest

measure of countries’ overall level of development and would thus capture any omitted

variables. Legal origin has been found to be an important factor in financial sector

development, with English legal origin countries generally displaying deeper financial

markets (La Porta et al., 1997). Capital account openness can be expected to influence

not only foreign investor demand, since they may otherwise not be able to access the

domestic market, but also that of domestic investors as it allows them to invest abroad.

At the same time, the degree of openness can be an important signal as to the country’s

own macroeconomic policies, with more closed economies being less subject to market

discipline, making domestic investors perhaps less interested in bonds.

Table 3 reports the regression results. We find that countries’ general level of

development, as proxied by GDP per capita, is actually statistically significant and

negatively related to the size of their domestic currency bond markets, and significant in

one specification for each of the other two dependent variables (columns 1 and 2). This

somewhat surprising result may in part be due to the fact that we already control in the

regression for a number of country factors⎯GDP, institutionalized democracy, inflation,

and fiscal policy. But importantly, the coefficients on these and other country variables

remain the same as above. This suggests that the relations found so far are not likely

driven by some relevant omitted country characteristics.

As documented by others, we confirm that countries with English legal origin

have relatively larger bond markets (Table 3, columns 3 and 4). English legal origin

24

countries have more developed domestic and foreign currency bond markets, suggesting

that the fact that a country has an English legal origin provides some comfort to investors,

perhaps as its legal system is more respectful of investors’ property rights and might treat

investors better in case of default. In relative terms though, the legal origin is more

important for the domestic currency bond markets as the sign of the coefficient for the

share of foreign currency bonds is negative, although statistically significant in only one

of the two specifications. Again, the coefficients for the other variables remain the same

as above.

Regarding capital account openness, we use the variable constructed by Chinn

and Ito (2005). The results suggest that more open countries have less developed

domestic currency bond markets but have larger foreign currency bond markets (Table 3,

columns 5 and 6). This is consistent with domestic investors being less restricted in their

asset allocation under an open capital account and no financial restrictions, leading them

to demand less domestic currency debt. Similarly, foreign investors are more likely to

invest in a country’s bonds when its financial market is open, but they do so by

purchasing foreign currency bonds, as discussed above. In terms of the share of foreign

exchange bonds, the sign on the capital account openness variable is then also positive

(and statistically significant). Also in these specifications, the coefficients for the other

variables remain the same as above.

Third, our results so far suggest that there are some economies of scale in the

development of bond markets as the sign for the coefficient on the size of the economy

(log of GDP) is consistently positive in the domestic currency bond market regressions

and negative in the foreign currency bond market regressions. We now explore whether

25

there are some non-linear effects, i.e., whether the tendency to use foreign currency

bonds depends on the economic size. The idea is that it might be difficult for very small

countries to borrow in foreign currency, for example because investors do not want to

invest resources in analyzing the prospects of the country. Since this is an empirical

question, we tested whether the relation is hump-shaped by including a quadratic term.

The results of the non-linear effects of size are reported in Table 4. We do find

some support for an inverted U-shape relation, as the sign for the log of GDP is positive

for foreign exchange bonds both as a ratio of GDP and as a share of total government

bonds, while the sign for the square of log of GDP is negative. All other country

variables have the same sign and significance as above, confirming the robustness of our

results on the importance of institutional and macroeconomic factors.

Fourth, another concern might be that use of the inflation index from the Heritage

Foundation rather than the inflation rate itself affects our results. We therefore also tried

different measures of inflation. We report results with the average past inflation over a

three-year period in Table 5. All the results using this measure instead of the index are

consistent with those using the index variable, except for domestic currency bonds, where

the average inflation is not statistically significant.29 The coefficients for all other

variables have the same sign and significance as above, confirming again the robustness

of the results.

Fifth, we analyze in greater detail the possibility of endogeneity of some of our

variables to the structure of a country’s liabilities. We concentrate especially on the

exchange rate regime, but we also consider the potential endogeneity of inflation and

fiscal burden. We have dealt with this problem to some extent by using lagged dependent

26

variables and initial values. We now do so in two other ways. Table 6 reports new

results that repeat earlier regressions, but without using the exchange rate regime to avoid

reaching conclusions based on potentially biased estimates. We find that the above

conclusions are unaltered. In Table 7, we instrument the actual exchange regime in two

regressions (columns 1 and 2) and the exchange rate regime, the inflation index, and the

fiscal burden in two other regressions (columns 3 and 4). We use as instruments lagged

values of these variables, where the instruments vary across specifications. Our results

that institutional and macroeconomic variables matter hold in the same manner as above:

countries with less flexible exchange regimes have relative more use of foreign currency

bonds, while lower inflation and higher fiscal burden are related to greater domestic and

foreign currency bond markets.

It would be ideal to have other instruments that could address better the potential

endogeneity problem. In search for other instruments, we have tried several variables

suggested by the literature. But, given the nature of our data, it is very difficult to find

good instruments to estimate the first stage. Instruments that could be used for the

exchange rate regime or the inflation index typically work well with a large set of

countries, since they are institutional factors that are usually available on a cross-

sectional basis. In our case, we use panel data of around 30 countries. Estimates of the

first stage using only those countries tend to be imprecise, making those instruments

invalid. These potential instruments include indicators of the autonomy of the central

bank, colonial origin, trade and geographic factors, and settler mortality.

Despite the attempts to correct for the endogeneity problem, one could still argue

that the exchange rate regime can be affected by the proportion of foreign currency debt,

27

for example because of the fear of floating mentioned above. But even in that case, it is

difficult to rule out that the exchange rate regime affects the currency structure of debt.

This independent effect of the exchange rate regime on the debt currency composition

may be illustrated with the experiences of several Latin American countries, including

Argentina, Brazil, Colombia, Mexico, and Uruguay.

The evidence suggests that after countries moved from fixed to floating exchange

rate regimes, the sovereign and corporate sectors have responded by issuing more local

currency debt in the very recent past. Tovar (2005) argues that the adoption of flexible

exchange regimes by Latin American countries has facilitated the issuance of domestic

currency debt in international markets. The UN-ECLAC (2005), the IMF (2005), and

Borensztein, Eichengreen, and Panizza (2006) also discuss these trends.30 On the

corporate side, the exchange rate regime also seems to have an effect. Galiani, Levy

Yeyati, and Schargrodsky (2003) argue that Argentina’s currency board contributed to

the dollarization of firms’ balance sheets by fueling beliefs in an implicit exchange rate

guarantee that reduced firms’ willingness to pay the cost of hedging their positions.31 In

the case of Mexico, Martinez and Werner (2002) propose a similar argument. They test it

by analyzing the effects that the change from a fixed to a floating exchange rate regime in

December 1994 had on the currency composition of corporate debt and on firms’

currency mismatches. They find evidence supporting the view that this shift prompted

firms to reduce their exposure to exchange rate risk. In the case of Brazil, Rossi (2004)

finds that the number of firms exposed to currency risk is significantly lower during the

period of floating exchange rate than during the fixed exchange rate regime. While not

28

ruling out reverse causality, this type of evidence suggests that the exchange rate regime

is likely to be at least partially exogenous and affect the debt currency structure.

Finally, we tested (but not report here) the importance of many other variables.

These tests included the share of the population over 65 to account for pension

expenditures, the use of variables scaled by the U.S. inflation, measures of U.S. T-bill

yields, growth rates in the U.S., G-3, and G-7 countries, measures related to interest rate

parity conditions, exclusion of the financial development variables, and exclusion of the

inflation variable. Furthermore, we used the level of foreign currency reserves over GDP

to control, to some degree, for the ability of governments to repay outstanding bonds.

We also used interaction terms between the variables of interest and a dummy for

developed countries to test whether the effects of the explanatory variables differ across

developed and developing countries. Again, the inclusion of those variables does not

affect significantly our basic results and, in several cases, the new variables included are

statistically significant.

6. Conclusions

In this paper, we analyze which factors are related to government debt issuance in

domestic and foreign currency, in light of the limited ability of developing countries to

issue claims in their own currency and the recent debate on original sin. Consistent with

previous results, we find that smaller economies tend to have smaller domestic currency

bond markets but have larger amounts of bond financing in foreign currency. We also

show that, besides the size of the economy, a number of institutional and macroeconomic

29

factors are indeed related to the development of local currency bond markets and the use

of foreign currency ones.

Economies that have less developed domestic financial systems tend to have

relatively smaller amounts of bond financing in domestic currency, while larger foreign

demand is associated with more foreign currency bonds (as a share of both GDP and total

government bonds). The level of inflation, democratic institutions restricting government

actions, countries’ legal orientation, fiscal burden, financial liberalization, and other

institutional variables are related to the degree of domestic currency bond market

development and the use of foreign currency bonds. Moreover, countries with less

flexible exchange rate regimes have relatively more foreign currency financing. This

relation may be because of incentives in place, such as moral hazard considerations

arising from an international bailout, or because governments try to bind themselves to a

higher commitment on macroeconomic management.

Our findings have several implications for the current discussions on the

feasibility of developing domestic currency bond markets, especially for reducing

exposure to foreign exchange risk for emerging markets. The result that smaller

economies tend to issue more foreign currency denominated bonds suggests some scale

effects in the development of local currency bond markets, perhaps due to the fixed costs

of establishing the infrastructure or because of externalities in liquidity. This implies that

there may be some limits to the development of local bond markets in domestic currency,

especially for small economies. The findings also highlight the importance of the role of

the overall domestic financial system in developing bond markets. Specifically, a well

developed financial system with a relatively large pool of domestic investors may help to

30

develop local currency debt markets, given that domestic investors are the ones that tend

to demand domestic currency debt. And since foreign investors mostly demand foreign

currency debt, issuing domestic currency debt catered to international investors remains

difficult, though not impossible. As many countries are small and have limited domestic

investor bases, they have little choice but to issue foreign currency claims to foreign

investors and incur the associated higher exchange rate risk.

Our results also suggest that policies seem to matter. The fact that more flexible

regimes can support a greater share of domestic currency bonds is consistent with the

claim that more rigid exchange rate regimes generate incentives to borrow in foreign

currency, exposing countries to more foreign exchange risk. This implies that, in terms

of risks, the exchange rate regime might be important as it affects the incentive structure

to borrow in foreign currency. More generally, the policy implication of our results is

that the whole institutional and macroeconomic structure, including not only the

exchange rate regime but also the monetary, financial, and fiscal stance, can determine

the degree of risk taking of a country. In that respect, the very recent experiences

mentioned in this paper, with Chile, Colombia, Mexico, and other countries actively

issuing domestic currency bonds in domestic and international capital markets, might

offer some hope for other emerging economies with a high degree of dollarization. In

these recent experiences, macroeconomic fundamentals appear to have played an

important role in enabling access to domestic currency financing.

While this paper has provided inputs into the analysis of government bond

markets, many issues remain open for future research. On the methodology front,

research can continue to investigate whether good instruments exist to test and control for

31

potential endogeneity. We tried to address this issue by, among other things, using lags

and initial values and instrumental variables regressions, as well as excluding the

exchange rate regime; but it is still possible that we have not been fully successful in

addressing this problem. Moreover, it would be interesting to analyze why our results are

different from those of the original sin literature. Perhaps, the inclusion by that literature

of many other countries with little or no bond market activity explains those differences.

Finally, it would be useful to study to what extent supply-side and demand-side factors

drive our results. Our results suggest that the domestic investor base is very important to

develop domestic currency bond markets and help countries overcome the original sin,

but more research is needed on this front.

32

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Handbook, Washington, D.C., 2001. Notes

1 See Persson and Tabellini (1999) and Walsh (1998) for recent reviews, as well as

Reinhart, Rogoff, and Savastano (2003) for a new perspective on the topic.

2 See Eaton and Fernandez (1995) for a review.

3 Perhaps the first study was Edwards (1986), but since has evolved into a large literature

mostly focusing on secondary market prices, with some studies on primary issues (e.g.,

Eichengreen and Mody, 1998).

4 See Broner, Lorenzoni, and Schmukler (2004) for a study of the maturity structure of

government bonds and the references therein.

5 A related literature has analyzed the development of government bond markets. This

literature highlights many of the institutional determinants of government and corporate

bond markets using experiences based mostly on developed countries. See Turner (2002)

for an overview, and World Bank and International Monetary Fund (2001), Bank for

International Settlements (2002), and International Organization of Securities

Commissions (2002) for institutional reports. This literature stresses, among other

factors, the importance of proper debt management and other institutional requirements,

including public governance. See De Broeck, Guillaume, and Van der Stichele (1998),

37

McCauley (1999), Schinasi and Smith (1998), Scott (2000), and Santos and Tsatsaronis

(2003).

6 Flandreau and Sussman (2005) find that European countries with a large presence in

international trade in the nineteenth century were able to issue bonds in domestic

currency abroad, irrespective of the quality of their institutions, because there was a spot

and futures market for their currencies. Therefore, they argue that overcoming original

sin requires that a country emerge as a leading economic power, as exemplified by the

U.S. in the nineteenth century and Japan in the twentieth century.

7 Eichengreen, Hausmann, and Panizza (2002) argue that the only way for emerging

markets to escape the original sin is an international initiative to develop a market for

claims denominated in an emerging market currency index, by having multilateral

financial institutions and G-10 countries issuing debt denominated in this index.

8 Although some of these instruments are often called sovereign bonds, we prefer to use

the term government bonds to make clear that we include both central government as

well as local government bonds, though most bonds in our sample are issued by central

governments.

9 See de la Torre and Schmukler (2004).

10 The level of debt (especially external debt) has been identified as a significant

determinant of interest rate spreads (Edwards, 1986; Eichengreen and Mody, 1998; and

Min, 1998), credit ratings (Cantor and Packer, 1996), and defaults and financial crises

(Rodrik and Velasco, 1999; Detragiache and Spilimbergo, 2001; and Manasse, Roubini,

and Schimmelpfennig, 2003). On the other hand, some authors have argued that the

development of a government bond market is necessary to foster the growth of a private

38

bond market, which in turn could make countries less vulnerable to financial crises by

reducing dependence on bank financing. See, for example, Herring and Chatusripitak

(2000), Asian Development Bank (2001), and International Finance Corporation (2001).

11 We use different measures of foreign investor participation because of the difficulty in

capturing foreign investor demand. To choose the variables, we partly follow Burger and

Warnock (2004) and Lane (2005).

12 Potentially, selectivity bias might be a problem, but in our case, we do not think that

this is an important issue. The data set we use contains a wide range of economies

selected by the BIS, which have significant bond markets. Though some countries not

included in the sample probably also issue bonds, the BIS does not report that

information. A Heckman-type estimator would estimate the decision of the BIS to report

data on certain countries, but it would not estimate the typical selection bias of only

observing data of countries that do issue bonds.

13 The classification takes into account the formal currency denomination of bonds. For

example, indexed domestic currency bonds are considered domestic currency debt.

14 The small participation of emerging economies in global markets is not driven by the

relatively small number of emerging economies in the sample, as we cover 12 of the

largest emerging markets. For comparison, eight of these 12 countries are part of the

emerging market bond index (EMBI+), compiled by J.P. Morgan, which contains a total

of 19 countries. These eight countries account for 80 percent of the combined GDP of

the 19 countries in the EMBI+ in 2000. Moreover, four emerging markets not part of the

EMBI+ but included in our data (Chile, China, the Czech Republic, and South Korea) are

all large emerging markets.

39

15 The impact of the introduction of the Euro is one factor reducing arithmetically the

share of foreign denominated bonds among the EMU members, but comparing pre- and

post-January 1, 1999 figures shows that this fact does not affect the figures significantly.

16 Summary statistics of debt stocks relative to GDP are shown in Appendix Table 1,

grouped by developed and emerging economies and evaluated at three points in time,

1993, 1996, and 2000. Appendix Table 2 lists the countries included in each group.

17 Note that the inclusion of debt at all maturities probably explains why the bond market

in Brazil appears more developed market than those in Germany or the Netherlands;

Brazil has a very large short-term debt market.

18 We estimated all the regressions excluding Luxembourg and obtained results similar to

those reported in the paper.

19 An alternative variable to measure the potential domestic demand is the size of

institutional investors. But the data coverage on this variable would have reduced the

sample size substantially, so we decided not to use it.

20 For example, Hausmann, Gavin, Pages-Serra, and Stein (2000) argue that in economies

facing important terms of trade shocks, a fixed exchange rate regime increases financial

intermediation in local currency by generating a negative covariance between domestic

asset prices and the income process.

21 McCauley and Remolona (2000) find that there may be a size threshold around 100-

200 billion U.S. dollars of outstanding domestic government bonds, below which

sustaining a liquid government bond market may not be easy.

22 See Reinhart, Rogoff, and Savastano (2003) for a related argument why the ratio of

debt to GDP differs across countries.

40

23 Given that these data are available for only one point in time (1997), we repeated the

values for all the years in our sample. The survey was conducted again in 2001, but we

could not use these data as our sample covers the period 1993-2000. For a description of

the benchmark survey, see Griever, Lee, and Warnock (2001).

24 Alternatively, we ran all the regressions using data from Thomas, Warnock, and

Wongswan (2004), who estimate U.S. investors’ foreign bond holdings for the period

1973-2003, and obtained in most cases similar results.

25 These data are also measured at one point in time (1997). As in the other case, we

repeated the values for all the years in our sample. Data are also available for 2001.

26 These data are similar to those reported in the benchmark survey of U.S. investment

abroad, but covering more countries may provide a better estimate of foreign investor

demand than just focusing on U.S. investors. Note that data quality may differ across

countries, as most countries did not carry out a fully fledged survey. (We than Frank

Warnock for bringing this issue to our attention.) Nevertheless, results for this variable

are similar to those for other proxies for international investor demand.

27 Lane and Milesi-Ferretti (2004) use data from the CPIS to analyze bilateral equity

holdings.

28 Those results are reported in the working paper version of this paper.

29 We also found some evidence that it matters whether countries cross certain levels of

inflation, and not necessarily the level of inflation per se. This is consistent with the

results previously reported by Boyd, Levine, and Smith (2001), who find that the relation

between inflation and financial development is characterized by the existence of

41

thresholds. Perhaps, this might explain why the index works well, since it ranks

countries in five categories, rather than as a continuous variable.

30 Apart from Latin America and with a more historical perspective, Bordo, Meissner,

and Redish (2005) analyze the experience of a number of former British colonies (United

States, Canada, Australia, New Zealand, and South Africa) and highlight the role of

shocks such as the breakdown of the Bretton Woods system in overcoming original sin in

these countries.

31 See Galindo, Panizza, and Schiantarelli (2003) for a review of the empirical evidence

on the determinants of the currency composition of corporate debt in Latin America.

This figure shows the evolution of the amount outstanding of foreign currency denominated government bonds over the totalamount outstanding of government bonds. The series are averages across countries, divided in developed countries and emergingmarkets following the classification used by the International Monetary Fund World Economic Outlook at the beginning of theperiod under study (see Appendix Table 2).

Figure 2

Share of Foreign Currency Government Bonds

Figure 1

This figure shows the evolution of the amount outstanding of government bonds in billions of U.S. dollars. Bonds are issued in local and foreign currencies in domestic and international markets.

Evolution of Government Bond Markets

0

4,000

8,000

12,000

16,000

20,000

1993 1994 1995 1996 1997 1998 1999 2000

Developed Countries Emerging Markets

0%

5%

10%

15%

20%

25%

30%

1993 1994 1995 1996 1997 1998 1999 2000

Developed Countries Emerging Markets

Bil

lion

s of

U.S

. dol

lars

This figure shows the amount outstanding of government bonds for 35 countries (23 developed and 12 emerging) as of December 31, 2000.Bonds are issued in local and foreign currencies in domestic and international markets. Countries are divided in developed countries andemerging markets following the classification used by the International Monetary Fund World Economic Outlook at the beginning of the periodunder study (see Appendix Table 2).

Figure 3

Composition and Participants of Government Bond Markets

Developed countries

95%

Emerging markets5%

Foreign currency

2%

Local currency

98%

Foreign currency

20%

Local currency

83%

Italy6%

Others20%

Japan26%

United States48%

Canada21%

Italy14%

Others52%

Sweden13%

Brazil30%

China28%

Others33%

South Korea

9%

Brazil13%

Others30%

Mexico15%

Argentina42%

World government bond market$19,082 billion

Largest local currency participants

$17,649 billion

Developed countriesby currency

$18,046 billion

Emerging marketsby currency

$1,036 billion

Largest foreigncurrency participants

$397 billion

Largest localcurrency participants

$826 billion

Largest foreigncurrency participants

$211 billion

Figure 5

Country Ranking Based on Share of Foreign Currency Government Bonds

This figure shows the amount outstanding of foreign currency denominated government bonds over the total amountoutstanding of government bonds. Countries are ranked in descending order as of December 31, 2000.

Figure 4

This figure shows the amount outstanding of government bonds over GDP. Countries are ranked in descending order as ofDecember 31, 2000. Data are divided in two categories based on the currency of issuance.

Country Ranking Based on Government Bonds / GDP

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

110%

Bel

gium Ital

y

Japa

n

Gre

ece

Uni

ted

Stat

es

Can

ada

Swed

en

Aus

tria

Den

mar

k

Finl

and

Spai

n

Fran

ce

Port

ugal

Bra

zil

Net

herl

ands

Sout

h A

fric

a

Ger

man

y

Icel

and

Tur

key

Cze

ch R

epub

lic

New

Zea

land

Mal

aysi

a

Arg

enti

na

Uni

ted

Kin

gdom

Chi

le

Irel

and

Sing

apor

e

Aus

tral

ia

Chi

na

Pola

nd

Nor

way

Sout

h K

orea

Mex

ico

Rus

sia

Lux

embo

urg

Foreign currency denominated government bonds

Local currency denominated government bonds

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Arg

enti

na

Lux

embo

urg

Rus

sia

Icel

and

Mex

ico

Finl

and

Swed

en

Tur

key

Aus

tria

New

Zea

land

Irel

and

Can

ada

Den

mar

k

Port

ugal

Gre

ece

Aus

tral

ia

Sout

h K

orea

Bra

zil

Mal

aysi

a

Spai

n

Sout

h A

fric

a

Nor

way

Ital

y

Chi

na

Bel

gium

Pola

nd

Uni

ted

Kin

gdom

Chi

le

Fran

ce

Sing

apor

e

Cze

ch R

epub

lic

Japa

n

Uni

ted

Stat

es

Net

herl

ands

Ger

man

y

Independent variables:

Log of GDP 0.092 *** 0.172 *** 0.182 *** 0.092 *** 0.206 *** 0.103 ***[6.028] [6.270] [11.142] [3.130] [8.584] [3.111]

Log of total deposits / GDP 0.478 *** 0.367 *** 0.262 *** 0.643 *** 0.511 *** 0.435 ***[11.120] [5.768] [4.010] [14.148] [8.941] [7.316]

Institutionalized democracy 0.086 *** 0.081 *** 0.090 *** 0.090 *** 0.071 *** 0.044[9.514] [5.967] [2.670] [5.505] [2.959] [1.465]

Inflation index -0.010 -0.042 ** -0.066 *** 0.055 -0.112 *** -0.166 ***[0.759] [2.561] [3.850] [1.214] [3.157] [4.230]

Fiscal burden 0.110 *** 0.072 *** 0.067 ** 0.357 *** 0.113 -0.105[4.603] [2.907] [2.407] [3.659] [1.522] [1.578]

Official exchange rate regime 0.125 *** 0.264 ***[7.236] [6.221]

Actual exchange rate regime 0.002 0.057 *** 0.080 *** 0.194 ***(columns 2 and 5 RR, columns 3 and 6 LYS) [0.489] [3.064] [8.188] [4.184]

Observations 157 179 161 220 252 236Number of Countries 30 35 32 30 35 33

Independent variables:Log of GDP -0.944 *** -0.570 *** -0.733 *** -1.111 *** -0.763 *** -0.842 ***

[11.930] [8.435] [12.634] [15.912] [9.317] [9.778]Log of total deposits / GDP -0.389 *** -1.253 *** -1.091 *** -0.339 *** -0.376 *** -0.368 ***

[3.141] [10.766] [10.667] [3.145] [2.715] [2.810]Institutionalized democracy 0.249 *** 0.111 *** 0.160 *** 0.203 *** 0.154 *** 0.178 ***

[5.740] [3.706] [3.245] [4.711] [3.379] [3.303]Inflation index 0.043 -0.085 *** -0.086 *** -0.104 -0.043 -0.155

[1.361] [2.581] [3.088] [0.884] [0.386] [1.369]Fiscal burden 0.065 0.342 *** 0.422 *** -0.148 0.306 * 0.738 ***

[1.441] [5.352] [6.238] [0.460] [1.680] [3.504]Official exchange rate regime 0.113 ** 0.325 ***

[2.407] [3.733]Actual exchange rate regime -0.074 *** -0.102 * -0.124 *** -0.269 *(columns 2 and 5 RR, columns 3 and 6 LYS) [4.490] [1.801] [4.034] [1.807]

Observations 157 179 161 220 252 236Number of Countries 30 35 32 30 35 33

Independent variables:Log of GDP -1.043 *** -0.873 *** -0.947 *** -0.970 *** -0.805 *** -0.829 ***

[16.561] [16.730] [20.456] [15.056] [14.413] [13.467]Log of total deposits / GDP -1.007 *** -0.887 *** -1.114 *** -0.726 *** -0.645 *** -0.638 ***

[11.938] [8.986] [16.312] [7.197] [6.918] [7.287]Institutionalized democracy 0.095 ** 0.103 *** 0.095 *** 0.114 ** 0.111 ** 0.088 *

[2.572] [5.275] [5.911] [2.319] [2.161] [1.774]Inflation index -0.019 -0.091 *** -0.068 *** -0.118 ** -0.219 *** -0.141 **

[0.800] [4.321] [3.926] [2.090] [4.662] [2.386]Fiscal burden 0.029 0.081 * 0.236 *** -0.243 0.236 0.374 **

[0.739] [1.930] [4.742] [1.424] [1.335] [2.315]Official exchange rate regime 0.083 *** 0.075

[3.292] [0.852]Actual exchange rate regime -0.037 *** -0.092 ** -0.118 *** -0.418 ***(columns 2 and 5 RR, columns 3 and 6 LYS) [4.068] [2.490] [6.062] [4.208]

Observations 157 179 161 220 252 236Number of Countries 30 35 32 30 35 33

Table 1

Log of Local Currency Government Bonds Outstanding / GDP

Log of Foreign Currency Government Bonds Outstanding / GDP

Log of Foreign Currency Government Bonds Outstanding / Total Government Bonds Outstanding

Determinants of Government Bond Market DevelopmentThis table shows regressions estimated through FGLS with heteroskedastic error structures and autocorrelation within countries. The data cover 35 countries between1993 and 2000. For columns (1)-(3) inflation index, fiscal burden, and the three exchange rate regimes are lagged one period; for columns (4)-(6) the same variables areexpressed as their initial values of the time series. See Appendix Table 3 for the definition of the variables. Absolute values for z-statistics are in brackets. *, **, and ***mean significance at ten, five, and one percent, respectively.

Lagged variables Initial values

Lagged variables Initial values

Lagged variables Initial values

(1) (2) (3) (4) (5) (6)

(1) (2) (3) (4) (5) (6)

(5) (6)(1) (2) (3) (4)

Independent variables:

Log of GDP 0.251 *** 0.187 *** 0.134 *** 0.120 *** 0.057 *** 0.038 * 0.084 *** 0.066 ***[13.927] [10.424] [7.339] [3.135] [3.398] [1.683] [3.871] [2.892]

Log of total deposits / GDP 0.383 *** 0.245 *** 0.362 *** 0.266 *** 0.836 *** 0.798 *** 0.784 *** 0.732 ***[7.268] [4.128] [5.450] [3.690] [15.586] [16.007] [15.441] [14.111]

Log of stock market capitalization / GDP 0.161 *** 0.190 ***[7.122] [6.800]

International investor demand 0.089 *** 0.086 ** 0.099 *** 0.122 *** 0.103 *** 0.093 **[2.915] [2.323] [3.040] [3.472] [2.696] [2.361]

Institutionalized democracy 0.078 *** 0.118 *** 0.188 *** 0.193 *** 0.105 *** 0.096 *** 0.103 *** 0.109 ***[4.401] [4.591] [3.113] [2.693] [10.626] [5.355] [4.300] [4.760]

Inflation index -0.001 -0.002 -0.069 *** -0.063 *** 0.002 -0.002 -0.025 -0.023 *[0.048] [0.123] [4.326] [3.061] [0.193] [0.141] [1.750] [1.736]

Fiscal burden 0.049 ** 0.017 0.107 *** 0.080 *** 0.062 *** 0.085 *** 0.030 0.050 **[2.135] [0.583] [3.883] [2.622] [3.336] [3.928] [1.531] [2.399]

Actual exchange rate regime 0.001 0.038 ** 0.029 *** 0.031 * 0.000 0.007 0.009 *** 0.035 ***(odd columns RR, even columns LYS) [0.324] [2.224] [4.797] [1.682] [0.097] [0.508] [2.544] [2.724]

Observations 175 161 123 112 171 153 177 159Number of Countries 34 32 24 22 33 30 34 31

Independent variables:Log of GDP -0.679 *** -0.863 *** -0.721 *** -0.800 *** -0.588 *** -0.701 *** -0.710 *** -0.777 ***

[9.145] [16.233] [10.114] [12.381] [7.474] [10.187] [8.868] [9.878]Log of total deposits / GDP -1.311 *** -0.957 *** -1.216 *** -0.955 *** -0.728 *** -0.552 *** -0.600 *** -0.686 ***

[9.078] [8.591] [7.619] [5.126] [5.318] [3.936] [4.451] [5.731]Log of stock market capitalization / GDP -0.095 0.042

[1.289] [0.490]International investor demand 0.607 *** 0.958 *** 0.406 *** 0.649 *** 0.462 *** 0.975 ***

[10.282] [15.408] [3.982] [7.860] [2.847] [6.287]Institutionalized democracy 0.127 *** 0.175 *** 0.044 -0.044 0.209 *** 0.220 *** 0.167 *** 0.135 ***

[3.912] [4.175] [0.822] [0.806] [7.862] [6.680] [5.393] [3.941]Inflation index -0.102 *** -0.072 *** -0.098 -0.122 -0.024 -0.066 * 0.008 0.006

[2.894] [3.224] [2.078] [2.170] [0.578] [1.828] [0.218] [0.173]Fiscal burden 0.335 *** 0.438 *** 0.007 0.005 0.125 ** 0.238 *** 0.165 *** 0.292 ***

[5.209] [7.547] [0.187] [0.110] [2.231] [3.670] [2.922] [4.663]Actual exchange rate regime -0.077 *** -0.134 ** -0.110 -0.040 -0.048 *** -0.089 ** -0.028 ** -0.038(odd columns RR, even columns LYS) [4.969] [2.259] [6.933] [0.807] [3.349] [1.996] [2.002] [0.922]

Observations 175 161 123 112 171 153 177 159Number of Countries 34 32 24 22 33 30 34 31

Independent variables:Log of GDP -0.903 *** -0.965 *** -0.796 *** -0.979 *** -0.610 *** -0.693 *** -0.708 *** -0.725 ***

[21.008] [18.889] [12.497] [13.935] [11.263] [10.016] [12.961] [13.150]Log of total deposits / GDP -0.954 *** -1.132 *** -0.905 *** -0.950 *** -1.128 *** -1.124 *** -0.842 *** -1.220 ***

[10.084] [14.754] [5.989] [5.306] [10.475] [10.984] [7.333] [16.235]Log of stock market capitalization / GDP -0.088 ** -0.022

[1.993] [0.540]International investor demand 0.473 *** 0.550 *** 0.374 *** 0.371 *** 0.547 *** 0.638 ***

[7.115] [6.383] [4.594] [3.303] [5.627] [5.743]Institutionalized democracy 0.106 *** 0.096 *** -0.089 -0.293 *** 0.098 *** 0.114 *** 0.048 ** -0.007

[5.413] [5.021] [1.376] [2.635] [4.187] [4.051] [2.085] [0.328]Inflation index -0.122 *** -0.064 *** -0.043 -0.216 *** -0.060 ** -0.054 * -0.042 -0.016

[6.481] [3.227] [1.190] [6.108] [2.139] [1.733] [1.664] [0.645]Fiscal burden 0.079 ** 0.258 *** 0.045 0.052 0.052 0.179 *** 0.104 ** 0.299 ***

[2.057] [5.091] [1.126] [0.994] [1.244] [3.156] [2.014] [5.096]Actual exchange rate regime -0.042 *** -0.107 *** -0.039 *** -0.003 -0.038 *** -0.083 ** -0.025 *** -0.070 **(odd columns RR, even columns LYS) [4.945] [2.841] [2.980] [0.094] [3.993] [2.276] [2.787] [2.151]

Observations 175 161 123 112 171 153 177 159Number of Countries 34 32 24 22 33 30 34 31

(3) (4) (5) (6)Log of Local Currency Government Bonds Outstanding / GDP

Log of Foreign Currency Government Bonds Outstanding / GDP

Log of Foreign Currency Government Bonds Outstanding / Total Government Bonds Outstanding

Table 2

Alternative Estimates - Domestic Stock Markets and International Investor DemandThis table shows regressions estimated through FGLS with heteroskedastic error structures and autocorrelation within countries. The data cover 35 countries between 1993 and 2000. In columns (3)and (4) the international investor demand variable is the logarithm of the government bonds and notes held by non-residents over GDP. In columns (5) and (6) the international investor demandvariable is the logarithm of the long-term debt securities held by U.S. investors over GDP in 1997. In columns (7) and (8) the international investor demand variable is the logarithm of total debtsecurities held by foreign investors over GDP in 1997. Inflation index, fiscal burden, and the two exchange rate regimes are lagged one period. See Appendix Table 3 for the definition of thevariables. Absolute values for z-statistics are in brackets. *, **, and *** mean significance at ten, five, and one percent, respectively.

(1) (2) (7) (8)

(1) (2) (7) (8)(3) (4) (5) (6)

(1) (2) (7) (8)(3) (4) (5) (6)

\

Independent variables:Log of GDP 0.177 *** 0.255 *** 0.143 *** 0.217 *** 0.053 *** 0.081 ***

[6.555] [10.095] [5.660] [12.855] [3.074] [4.031]Log of total deposits / GDP 0.379 *** 0.339 *** 0.400 *** 0.309 *** 0.666 *** 0.581 ***

[5.476] [4.944] [6.332] [5.380] [12.345] [10.702]Log of GDP per capita -0.139 *** -0.282 ***

[3.036] [5.478]English legal origin 0.521 *** 0.625 ***

[8.240] [11.528]Capital account openess -0.057 *** -0.069 ***

[2.872] [3.547]Institutionalized democracy 0.116 *** 0.199 *** 0.115 *** 0.066 *** 0.122 *** 0.109 ***

[6.977] [5.408] [6.631] [3.174] [12.712] [7.899]Inflation index -0.085 *** -0.082 *** -0.009 -0.032 *** -0.030 * -0.037 **

[4.408] [3.870] [0.548] [2.821] [1.687] [2.167]Fiscal burden 0.102 *** 0.121 *** 0.077 *** 0.088 *** 0.155 *** 0.158 ***

[3.702] [3.987] [3.304] [3.214] [6.658] [5.114]Actual exchange rate regime 0.004 0.026 -0.003 0.014 0.011 * 0.079 ***(odd columns RR, even columns LYS) [0.904] [1.408] [0.666] [0.856] [1.883] [4.407]

Observations 179 161 179 161 119 111Number of Countries 35 32 35 32 28 26

Independent variables:Log of GDP -0.498 *** -0.709 *** -0.594 *** -0.637 *** -0.750 *** -0.952 ***

[8.648] [11.011] [10.173] [10.531] [15.098] [19.378]Log of total deposits / GDP -1.026 *** -1.033 *** -1.173 *** -1.099 *** -0.624 *** -0.545 ***

[8.729] [7.589] [9.083] [10.219] [4.982] [4.241]Log of GDP per capita -0.443 *** -0.104

[3.401] [0.754]English legal origin 0.522 *** 0.073

[2.864] [0.441]Capital account openess 0.240 *** 0.222 ***

[4.073] [3.020]Institutionalized democracy 0.232 *** 0.185 *** 0.126 *** 0.062 0.451 *** 0.500 ***

[5.124] [3.129] [3.890] [1.589] [11.176] [13.741]Inflation index -0.108 *** -0.092 *** -0.074 ** -0.092 ** 0.132 *** 0.121 **

[3.142] [3.143] [2.049] [2.481] [3.290] [2.505]Fiscal burden 0.316 *** 0.410 *** 0.352 *** 0.391 *** 0.152 ** 0.163 **

[5.005] [5.855] [5.204] [5.207] [2.294] [2.058]Actual exchange rate regime -0.077 *** -0.113 * -0.072 *** -0.082 -0.053 *** 0.004(odd columns RR, even columns LYS) [4.872] [1.928] [3.516] [1.228] [4.104] [0.113]

Observations 179 161 179 161 119 111Number of Countries 35 32 35 32 28 26

Independent variables:Log of GDP -0.876 *** -1.047 *** -0.906 *** -0.927 *** -0.886 *** -0.982 ***

[16.559] [17.352] [16.002] [17.748] [15.726] [16.037]Log of total deposits / GDP -0.948 *** -1.204 *** -0.826 *** -0.950 *** -0.842 *** -1.037 ***

[9.932] [13.512] [7.566] [11.796] [7.010] [8.164]Log of GDP per capita 0.003 0.467 ***

[0.036] [4.427]English legal origin -0.233 -0.802 ***

[1.475] [4.696]Capital account openess 0.162 *** 0.141 **

[3.928] [2.485]Institutionalized democracy 0.094 *** -0.005 0.094 *** 0.006 0.171 *** 0.258 ***

[3.491] [0.155] [3.202] [0.255] [6.505] [6.938]Inflation index -0.096 *** -0.020 -0.062 ** -0.096 *** 0.012 0.009

[5.175] [0.807] [2.429] [3.429] [0.422] [0.268]Fiscal burden 0.098 ** 0.223 *** 0.058 0.164 *** 0.203 *** 0.260 ***

[2.351] [3.965] [1.244] [3.047] [2.833] [3.529]Actual exchange rate regime -0.040 *** -0.062 * -0.034 *** -0.037 -0.064 *** -0.001(odd columns RR, even columns LYS) [4.360] [1.809] [3.193] [0.965] [4.821] [0.033]

Observations 179 161 179 161 119 111Number of Countries 35 32 35 32 28 26

(5) (6)(1) (2) (3) (4)

(5) (6)

(1) (2) (3) (4) (5) (6)

Table 3

Log of Local Currency Government Bonds Outstanding / GDP

Log of Foreign Currency Government Bonds Outstanding / GDP

Log of Foreign Currency Government Bonds Outstanding / Total Government Bonds Outstanding

This table shows regressions estimated through FGLS with heteroskedastic error structures and autocorrelation within countries. The data cover 35 countriesbetween 1993 and 2000. Inflation index, fiscal burden, and the two exchange rate regimes are lagged one period. See Appendix Table 3 for the definition ofthe variables. Absolute values for z-statistics are in brackets. *, **, and *** mean significance at ten, five, and one percent, respectively.

Alternative Estimates - GDP per capita, Legal Origin, and Capital Account Openess

(1) (2) (3) (4)

Inde

pend

ent v

aria

bles

:L

og o

f G

DP

4.76

0**

*7.

186

***

3.20

8**

*4.

399

***

[6.7

40]

[7.6

13]

[12.

631]

[5.6

20]

Squa

re lo

g of

GD

P-0

.216

***

-0.3

12**

*-0

.160

***

-0.2

06**

*[7

.657

][8

.364

][1

4.26

4][6

.686

]L

og o

f to

tal d

epos

its /

GD

P-0

.977

***

-0.4

84**

*-0

.992

***

-0.8

67**

*[7

.959

][3

.784

][1

3.02

2][1

1.88

4]In

stitu

tiona

lized

dem

ocra

cy0.

159

***

0.28

2**

*0.

101

***

0.10

9**

*[5

.792

][4

.851

][4

.596

][5

.001

]In

flat

ion

inde

x-0

.135

***

-0.1

30**

*-0

.120

***

-0.1

11**

*[4

.290

][5

.261

][7

.841

][7

.663

]F

isca

l bur

den

0.05

50.

110

**0.

043

0.07

0**

[1.1

70]

[2.2

81]

[1.6

08]

[2.0

27]

Act

ual e

xcha

nge

rate

reg

ime

(RR

)-0

.052

***

-0.0

31**

*[3

.876

][3

.678

]A

ctua

l exc

hang

e ra

te r

egim

e (L

YS)

-0.0

89*

-0.0

79**

[1.8

52]

[2.4

50]

Obs

erva

tions

179

161

179

161

Num

ber

of C

ount

ries

3532

3532

Tab

le 4

Alt

erna

tive

Est

imat

es -

Siz

e (n

on-l

inea

r ef

fect

s)T

his

tabl

esh

ows

regr

essi

ons

estim

ated

thro

ugh

FGL

Sw

ithhe

tero

sked

astic

erro

rst

ruct

ures

and

auto

corr

elat

ion

with

inco

untr

ies.

The

data

cove

r35

coun

trie

sbe

twee

n19

93an

d20

00.

Infl

atio

nin

dex,

fisc

albu

rden

,an

dth

etw

oex

chan

gera

tere

gim

esar

ela

gged

one

peri

od.S

eeA

ppen

dix

Tab

le3

for

the

defi

nitio

nof

the

vari

able

s.A

bsol

ute

valu

esfo

rz-

stat

istic

sar

ein

brac

kets

.*,*

*,an

d**

*m

ean

sign

ific

ance

at t

en, f

ive,

and

one

per

cent

, res

pect

ivel

y.

Log

of

Fore

ign

Cur

renc

y G

over

nmen

t B

onds

Out

stan

ding

/ T

otal

Gov

ernm

ent

Bon

ds O

utst

andi

ngL

og o

f Fo

reig

n C

urre

ncy

Gov

ernm

ent

Bon

ds O

utst

andi

ng /

GD

P(4

)(1

)(2

)(3

)

Inde

pend

ent v

aria

bles

:

Log

of

GD

P0.

211

***

0.18

9**

*-0

.573

***

-0.7

31**

*-0

.868

***

-0.9

03**

*[7

.676

][9

.987

][8

.186

][1

2.59

5][1

6.19

8][1

8.84

7]L

og o

f to

tal d

epos

its /

GD

P0.

424

***

0.39

3**

*-1

.225

***

-1.1

15**

*-0

.916

***

-1.1

73**

*[7

.277

][6

.635

][1

0.53

6][1

1.95

7][9

.208

][1

8.03

0]In

stitu

tiona

lized

dem

ocra

cy0.

054

***

0.06

5**

0.14

6**

*0.

172

***

0.12

3**

*0.

092

***

[2.9

46]

[2.2

03]

[4.0

91]

[3.2

80]

[5.8

66]

[4.8

67]

Infl

atio

n (t

hree

-yea

r av

erag

e)-0

.073

-0.0

60-0

.813

***

-0.6

30**

*-0

.522

***

-0.4

99**

*[0

.791

][0

.695

][8

.593

][5

.757

][5

.605

][6

.838

]F

isca

l bur

den

0.07

7**

*0.

091

***

0.30

7**

*0.

387

***

0.05

90.

260

***

[3.2

24]

[3.4

71]

[5.1

68]

[5.6

43]

[1.4

24]

[4.8

54]

Act

ual e

xcha

nge

rate

reg

ime

(RR

)0.

001

-0.0

72**

*-0

.037

***

[0.2

33]

[4.5

66]

[3.8

64]

Act

ual e

xcha

nge

rate

reg

ime

(LY

S)0.

028

*-0

.109

*-0

.068

*[1

.682

][1

.818

][1

.805

]

Obs

erva

tions

177

160

177

160

177

160

Num

ber

of C

ount

ries

3532

3532

3532

Tab

le 5

Alt

erna

tive

Est

imat

es -

Inf

lati

onT

his

tabl

esh

ows

regr

essi

ons

estim

ated

thro

ugh

FGL

Sw

ithhe

tero

sked

astic

erro

rst

ruct

ures

and

auto

corr

elat

ion

with

inco

untr

ies.

The

data

cove

r35

coun

trie

sbe

twee

n19

93an

d20

00.

Infl

atio

n,fi

scal

burd

en,a

ndth

etw

oex

chan

gera

tere

gim

esar

ela

gged

one

peri

od.S

eeA

ppen

dix

Tab

le3

for

the

defi

nitio

nof

the

vari

able

s.A

bsol

ute

valu

esfo

rz-

stat

isti

csar

ein

brac

kets

.*,

**,

and

***

mea

n si

gnif

ican

ce a

t ten

, fiv

e, a

nd o

ne p

erce

nt, r

espe

ctiv

ely.

Log

of

Fore

ign

Cur

renc

y G

over

nmen

t B

onds

Out

stan

ding

/ T

otal

Gov

ernm

ent

Bon

ds O

utst

andi

ngL

og o

f L

ocal

Cur

renc

y G

over

nmen

t Bon

ds

Out

stan

ding

/ G

DP

Log

of

Fore

ign

Cur

renc

y G

over

nmen

t B

onds

Out

stan

ding

/ G

DP

(1)

(2)

(1)

(2)

(3)

(4)

Independent variables:Log of GDP 0.160 *** 0.279 *** 0.159 *** 0.169 *** 0.132 *** 0.064 ***

[5.855] [15.931] [8.586] [6.350] [5.876] [4.210]Log of total deposits / GDP 0.352 *** 0.376 *** 0.123 ** 0.351 *** 0.395 *** 0.695 ***

[5.988] [7.103] [2.183] [5.657] [6.834] [12.986]Log of stock market capitalization / GDP 0.155 ***

[6.968]International investor demand 0.064 *

[1.775]Log of GDP per capita -0.140 ***

[3.042]English legal origin 0.484 ***

[8.037]Capital account openess -0.072 ***

[3.625]Institutionalized democracy 0.082 *** 0.064 *** 0.256 *** 0.119 *** 0.114 *** 0.123 ***

[5.723] [3.649] [3.666] [6.889] [6.685] [12.228]Inflation Index -0.042 ** 0.007 -0.070 *** -0.085 *** -0.018 -0.024

[2.547] [0.431] [3.701] [4.511] [1.110] [1.283]Fiscal burden 0.072 *** 0.061 *** 0.096 *** 0.103 *** 0.081 *** 0.165 ***

[2.831] [2.902] [3.107] [3.639] [3.410] [6.891]

Observations 179 175 123 179 179 119Number of Countries 35 34 24 35 35 28

Independent variables:Log of GDP -0.626 *** -0.682 *** -0.713 *** -0.526 *** -0.566 *** -0.874 ***

[12.673] [10.573] [10.828] [15.082] [11.744] [23.921]Log of total deposits / GDP -1.019 *** -1.174 *** -0.592 *** -0.724 *** -0.913 *** -0.496 ***

[11.333] [8.659] [3.917] [9.462] [10.240] [3.858]Log of stock market capitalization / GDP -0.003

[0.041]International investor demand 0.739 ***

[11.843]Log of GDP per capita -0.515 ***

[4.249]English legal origin 0.360 **

[2.543]Capital account openess 0.264 ***

[4.092]Institutionalized democracy 0.080 ** 0.093 *** -0.014 0.193 *** 0.082 ** 0.448 ***

[2.256] [2.658] [0.140] [4.399] [2.445] [13.264]Inflation Index -0.110 *** -0.109 *** -0.059 -0.123 *** -0.085 ** 0.156 ***

[2.909] [2.876] [1.258] [3.648] [2.243] [3.678]Fiscal burden 0.351 *** 0.283 *** 0.012 0.287 *** 0.266 *** 0.227 ***

[5.903] [4.114] [0.315] [4.868] [4.294] [3.014]

Observations 179 175 123 179 179 119Number of Countries 35 34 24 35 35 28

Independent variables:Log of GDP -0.862 *** -0.950 *** -0.753 *** -0.845 *** -0.954 *** -0.911 ***

[19.477] [18.518] [12.205] [17.581] [16.975] [17.050]Log of total deposits / GDP -0.918 *** -0.876 *** -0.666 *** -0.912 *** -0.832 *** -0.893 ***

[10.993] [10.442] [4.690] [10.879] [9.551] [7.180]Log of stock market capitalization / GDP -0.053

[1.267]International investor demand 0.487 ***

[7.134]Log of GDP per capita -0.038

[0.402]English legal origin -0.405 ***

[2.746]Capital account openess 0.224 ***

[3.485]Institutionalized democracy 0.074 ** 0.087 *** -0.048 0.080 ** 0.056 0.192 ***

[2.430] [3.127] [0.415] [2.191] [1.629] [6.777]Inflation Index -0.062 *** -0.078 *** -0.039 -0.067 *** -0.059 ** 0.095 **

[2.602] [2.930] [1.152] [2.709] [2.186] [2.405]Fiscal burden 0.068 0.057 0.068 0.070 0.058 0.286 ***

[1.453] [1.340] [1.452] [1.483] [1.236] [3.619]

Observations 179 175 123 179 179 119Number of Countries 35 34 24 35 35 28

(4) (5)

(1)

(6)

(6)

Log of Foreign Currency Government Bonds Outstanding / Total Government Bonds Outstanding(3)(1) (2)

(4)Log of Foreign Currency Government Bonds Outstanding / GDP

(2) (3) (5)

Table 6

Alternative Estimates - Excluding the Exchange Rate RegimeThis table shows regressions estimated through FGLS with heteroskedastic error structures and autocorrelation within countries. The data cover 35 countries between1993 and 2000. In column (3) the international investor demand variable is the logarithm of the government bonds and notes held by non-residents over GDP. Inflationindex and fiscal burden are lagged one period. See Appendix Table 3 for the definition of the variables. Absolute values for z-statistics are in brackets. *, **, and ***mean significance at ten, five, and one percent, respectively.

(1) (3)(2)Log of Local Currency Government Bonds Outstanding / GDP

(6)(4) (5)

Independent variables:

Log of GDP 0.157 *** 0.177 *** 0.083 *** 0.110 ***[5.611] [8.631] [3.011] [5.156]

Log of total deposits / GDP 0.378 *** 0.326 *** 0.672 *** 0.632 ***[5.936] [4.426] [10.585] [10.672]

Institutionalized democracy 0.078 *** 0.067 *** 0.076 *** 0.093 ***[5.764] [2.805] [3.265] [5.059]

Inflation index -0.040 ** -0.054 *** -0.057 *** -0.052 ***[2.463] [2.855] [2.725] [2.608]

Fiscal burden 0.076 *** 0.137 *** 0.081 *** 0.155 ***[3.083] [4.343] [2.647] [4.757]

Actual exchange rate regime 0.003 0.161 *** 0.000 0.083 ***(columns 1 and 3 RR, columns 2 and 4 LYS) [0.647] [4.979] [0.040] [3.367]

Observations 178 152 144 122Countries 35 31 33 28

Instruments Actual exchange rate regime (t-1; t-2) Inflation index (t-1; t-2) Fiscal burden (t-1; t-2) Actual exchange rate regime (t-1; t-2)

Independent variables:Log of GDP -0.563 *** -0.642 *** -0.738 *** -0.813 ***

[7.952] [7.969] [11.348] [10.070]Log of total deposits / GDP -1.306 *** -1.313 *** -0.879 *** -1.114 ***

[10.857] [9.746] [5.997] [7.592]Institutionalized democracy 0.126 *** 0.223 *** 0.139 *** 0.243 ***

[4.113] [4.093] [4.087] [5.680]Inflation index -0.085 ** -0.085 ** -0.113 ** -0.158 ***

[2.431] [2.174] [2.461] [3.738]Fiscal burden 0.307 *** 0.361 *** 0.325 *** 0.480 ***

[4.667] [4.902] [4.517] [5.810]Actual exchange rate regime -0.083 *** -0.514 *** -0.070 *** -0.614 ***(columns 1 and 3 RR, columns 2 and 4 LYS) [4.515] [4.605] [4.562] [6.969]

Observations 178 152 144 122Countries 35 31 33 28

Instruments Actual exchange rate regime (t-1; t-2) Inflation index (t-1; t-2) Fiscal burden (t-1; t-2) Actual exchange rate regime (t-1; t-2)

Independent variables:Log of GDP -0.882 *** -0.973 *** -0.792 *** -0.906 ***

[16.064] [14.259] [18.878] [17.933]Log of total deposits / GDP -0.928 *** -0.951 *** -1.146 *** -1.371 ***

[9.117] [9.807] [10.308] [14.611]Institutionalized democracy 0.113 *** 0.156 *** 0.051 * 0.135 ***

[5.524] [5.155] [1.917] [4.512]Inflation index -0.090 *** -0.085 *** -0.145 *** -0.151 ***

[4.045] [4.496] [5.240] [4.343]Fiscal burden 0.054 0.128 *** 0.236 *** 0.390 ***

[1.277] [2.810] [3.721] [5.374]Actual exchange rate regime -0.051 *** -0.296 *** -0.068 *** -0.431 ***(columns 1 and 3 RR, columns 2 and 4 LYS) [4.771] [3.930] [7.417] [6.717]

Observations 178 152 144 122Countries 35 31 33 28

Instruments Actual exchange rate regime (t-1; t-2) Inflation index (t-1; t-2) Fiscal burden (t-1; t-2) Actual exchange rate regime (t-1; t-2)

Log of Foreign Currency Government Bonds Outstanding / GDP(1)

Table 7

Alternative Estimates - Instrumental VariablesThis table shows regressions estimated through FGLS with heteroskedastic error structures and autocorrelation within countries. The datacover 35 countries between 1993 and 2000. In columns (1) and (2) the actual exchange rate regime is estimated from OLS regressions,using the macroeconomic and institutional variables and its own lags as regressors. In columns (3) and (4) the actual exchange rateregime, inflation index, and fiscal burden are estimated from OLS regressions, using the macroeconomic and institutional variables andtheir own lags as regressors. Since these variables are generated regressors in the FGLS regressions, the estimates of the standard errorsmay be biased. However, under the null hypothesis that the estimated coefficients are zero, the standard errors are unbiased. Therefore,the t-statistic for the null hypothesis is not invalidated (Pagan, 1984). Inflation index and fiscal burden are lagged one period. SeeAppendix Table 3 for the definition of the variables. Absolute values for z-statistics are in brackets. *, **, and *** mean significance atten, five, and one percent, respectively.

Log of Local Currency Government Bonds Outstanding / GDP(1) (2) (3) (4)

(1) (2) (3) (4)

(2) (3) (4)

Log of Foreign Currency Government Bonds Outstanding / Total Government Bonds

No.

Obs

.M

ean

Med

ian

Max

Min

Std.

Dev

.N

o. O

bs.

Mea

nM

edia

nM

axM

inSt

d. D

ev.

No.

Obs

.M

ean

Med

ian

Max

Min

Std.

Dev

.D

evel

oped

Cou

ntri

es21

0.46

0.37

1.01

0.00

0.26

220.

520.

421.

100.

000.

2723

0.48

0.45

1.02

0.00

0.28

Em

ergi

ng M

arke

ts9

0.23

0.11

0.66

0.10

0.20

100.

180.

150.

490.

030.

1412

0.23

0.24

0.42

0.02

0.14

Tot

al30

0.39

0.34

1.01

0.00

0.26

320.

410.

371.

100.

000.

2835

0.40

0.36

1.02

0.00

0.26

No.

Obs

.M

ean

Med

ian

Max

Min

Std.

Dev

.N

o. O

bs.

Mea

nM

edia

nM

axM

inSt

d. D

ev.

No.

Obs

.M

ean

Med

ian

Max

Min

Std.

Dev

.D

evel

oped

Cou

ntri

es21

0.10

0.07

0.37

0.00

0.10

220.

090.

060.

340.

000.

1023

0.06

0.05

0.22

0.00

0.07

Em

ergi

ng M

arke

ts9

0.02

0.01

0.06

0.00

0.02

100.

040.

010.

220.

000.

0712

0.06

0.03

0.31

0.00

0.08

Tot

al30

0.08

0.04

0.37

0.00

0.09

320.

080.

040.

340.

000.

0935

0.06

0.04

0.31

0.00

0.07

App

endi

x T

able

1

Sum

mar

y St

atis

tics

Thi

sta

ble

show

ssu

mm

ary

stat

isti

csof

loca

lcu

rren

cyde

nom

inat

edgo

vern

men

tbo

nds

outs

tand

ing

over

GD

Pan

dfo

reig

ncu

rren

cyde

nom

inat

edgo

vern

men

tbo

nds

outs

tand

ing

over

GD

P.

The

seri

esar

edi

vide

din

two

grou

ps(d

evel

oped

coun

trie

san

dem

ergi

ngm

arke

ts)

follo

win

gth

ecl

assi

fica

tion

used

byth

eIn

tern

atio

nal

Mon

etar

yFu

ndW

orld

Eco

nom

icO

utlo

okat

the

begi

nnin

gof

the

peri

odun

der

stud

y(s

eeA

ppen

dix

Tab

le2)

.T

hest

atis

tics

are

show

nfo

rth

ree

poin

tsin

time:

1993

,19

96,

and

2000

.T

hem

inim

umva

lues

that

appe

arw

ith

a0.

00ar

ege

nera

lly lo

w v

alue

s bu

t not

abs

olut

e ze

ros.

Loc

al C

urre

ncy

Gov

ernm

ent

Bon

ds O

utst

andi

ng /

GD

P

2000

For

eign

Cur

renc

y G

over

nmen

t B

onds

Out

stan

ding

/ G

DP

1993

1996

2000

1993

1996

Developed Countries Emerging Markets

Australia ArgentinaAustria BrazilBelgium ChileCanada ChinaDenmark Czech RepublicFinland MalaysiaFrance MexicoGermany PolandGreece RussiaIceland South AfricaIreland South KoreaItaly TurkeyJapanLuxembourgNetherlandsNew ZealandNorwayPortugalSingaporeSpainSwedenUnited KingdomUnited States

This table shows the list of countries in the database, divided into two groups following theclassification used by the International Monetary Fund World Economic Outlook at the beginning ofthe period under study (1993).

Appendix Table 2

Country Classification

Seri

es N

ames

Des

crip

tion

Sour

ce

Dep

ende

nt V

aria

bles

Loc

al a

nd fo

reig

n cu

rren

cy

deno

min

ated

gov

ernm

ent

bond

s ou

tsta

ndin

g (i

n cu

rren

t U

.S. d

olla

rs)

Am

ount

sou

tsta

ndin

gof

bond

s(i

nclu

ding

long

-ter

mbo

nds,

note

s,tr

easu

rybi

lls,

and

mon

ey-m

arke

tin

stru

men

ts)

issu

edby

the

publ

icse

ctor

deno

min

ated

inth

eir

own

loca

lcu

rren

cyan

din

fore

ign

curr

enci

esat

year

-end

valu

es.

The

publ

icse

ctor

incl

udes

all

gove

rnm

ent

leve

lsan

dst

ate

agen

cies

.Thi

sva

riab

leco

mpr

ises

issu

esin

allm

arke

ts(d

omes

tican

din

tern

atio

nal)

.Com

preh

ensi

veda

taar

eav

aila

ble

for

35co

untr

ies

from

1993

to20

00.

The

BIS

sour

ces

are:

Ban

kof

Eng

land

,C

apita

lD

AT

A,

Eur

ocle

ar,

ISM

A,

Tho

mso

nFi

nanc

ial

Secu

ritie

sD

ata,

and

natio

nal

sour

ces.

For

Arg

entin

a da

ta fr

om th

e M

inis

try

of F

inan

ce a

re u

sed

inst

ead.

Ban

k fo

r In

tern

atio

nal

Settl

emen

ts, I

nter

natio

nal

Fina

ncia

l Sta

tistic

s, a

nd th

e A

rgen

tine

Min

istr

y of

Fi

nanc

e

Shar

e of

fore

ign

curr

ency

de

nom

inat

ed g

over

nmen

t bo

nds

Thi

s ra

tio is

con

stru

cted

by

divi

ding

fore

ign

curr

ency

den

omin

ated

gov

ernm

ent b

onds

by

the

tota

l gov

ernm

ent b

onds

out

stan

ding

.B

ank

for

Inte

rnat

iona

l Se

ttlem

ents

, Int

erna

tiona

l Fi

nanc

ial S

tatis

tics

and

the

Arg

entin

e M

inis

try

of

Fina

nce

Inde

pend

ent V

aria

bles

GD

P at

mar

ket p

rice

s (i

n cu

rren

t U.S

. dol

lars

) G

ross

dom

estic

prod

uct

(GD

P)at

purc

hase

rpr

ices

.G

DP

data

isco

nver

ted

from

dom

estic

curr

enci

esus

ing

year

lyof

fici

alex

chan

gera

tes.

The

data

cove

r 35

cou

ntri

es fr

om 1

993

to 2

000.

The

Wor

ld B

ank,

Wor

ld

Dev

elop

men

t Ind

icat

ors

Fisc

al b

urde

n of

gov

ernm

ent

Fisc

albu

rden

ofgo

vern

men

tis

aco

mpo

nent

ofth

ein

dex

ofec

onom

icfr

eedo

mpu

blis

hed

byT

heH

erita

geFo

unda

tion

and

enco

mpa

sses

inco

me

tax

rate

s,co

rpor

ate

tax

rate

s,an

dgo

vern

men

texp

endi

ture

sas

perc

enta

geof

outp

ut.T

heva

riab

leis

afi

ve-c

ateg

ory

scal

ein

whi

chhi

gher

scor

esre

pres

ent

high

er le

vel o

f gov

ernm

ent e

xpen

ditu

re a

s pe

rcen

tage

of G

DP

and

high

er c

orpo

rate

tax

rate

s. T

he d

ata

cove

r 35

cou

ntri

es fr

om 1

994

to 2

001.

The

Her

itage

Fou

ndat

ion

Infl

atio

n in

dex

Infl

atio

nin

dex

isa

com

pone

ntof

the

inde

xof

econ

omic

free

dom

publ

ishe

dby

The

Her

itage

Foun

datio

n.T

heva

riab

leis

base

don

aco

untr

y’s

wei

ghte

dav

erag

ean

nual

infl

atio

nra

teov

erth

epr

evio

uste

nye

ars

and

has

afi

vepo

int

scal

e,w

here

high

erva

lues

repr

esen

thig

her

aver

age

infl

atio

nra

te o

r w

orse

mon

etar

y po

licy.

The

ori

gina

l nam

e of

the

vari

able

is m

onet

ary

polic

y. T

he d

ata

cove

r 35

cou

ntri

es fr

om 1

994

to 2

001.

The

Her

itage

Fou

ndat

ion

Inst

itutio

naliz

ed d

emoc

racy

Inst

itutio

naliz

edde

moc

racy

isco

ncei

ved

asth

ree

esse

ntia

l,in

terd

epen

dent

elem

ents

.One

isth

epr

esen

ceof

inst

itutio

nsan

dpr

oced

ures

thro

ugh

whi

chci

tizen

sca

nex

pres

sef

fect

ive

pref

eren

ces

abou

talte

rnat

ive

polic

ies

and

lead

ers.

Ano

ther

isth

eex

iste

nce

ofin

stitu

tiona

lized

cons

trai

nts

onth

eex

erci

seof

pow

erby

the

exec

utiv

e.T

heth

ird

one

isth

egu

aran

tee

ofci

vill

iber

ties

toal

lciti

zens

inth

eir

daily

lives

and

inac

tsof

polit

ical

part

icip

atio

n.O

ther

aspe

cts

ofpl

ural

dem

ocra

cy,

such

asth

eru

leof

law

,sy

stem

sof

chec

ksan

dba

lanc

es,

free

dom

ofth

epr

ess,

and

soon

are

mea

nsto

,or

spec

ific

man

ifes

tatio

nsof

,th

ese

gene

ral

prin

cipl

es.

The

inst

itutio

naliz

edde

moc

racy

indi

cato

ris

anad

ditiv

eel

even

-poi

ntsc

ale

(0-1

0).

The

data

cove

r35

coun

trie

s fr

om 1

993

to 2

000.

Polit

y IV

, IN

SCR

Pro

gram

, C

IDC

M, U

nive

rsity

of

Mar

ylan

d

Tot

al d

epos

its (

curr

ent U

.S.

dolla

rs)

Thi

sva

riab

leis

com

pose

dby

all

the

depo

sits

held

byco

mm

erci

alba

nks

and

othe

rfi

nanc

ial

inst

itutio

nsth

atac

cept

tran

sfer

able

depo

sits

incl

udin

gde

man

d,tim

e,an

dsa

ving

sde

posi

ts,a

ndde

posi

tsfr

omth

ego

vern

men

t.A

sth

eor

igin

alda

taar

eav

aila

ble

indo

mes

ticcu

rren

cy,t

heye

ar-e

ndm

arke

tex

chan

ge r

ates

are

use

d to

con

vert

the

vari

able

into

U.S

. dol

lars

. The

dat

a co

ver

35 c

ount

ries

from

199

3 to

200

0.

Inte

rnat

iona

l Mon

etar

y Fu

nd, I

nter

natio

nal

Fina

ncia

l Sta

tistic

s

Seri

es D

escr

ipti

on a

nd D

ata

Sour

ces

App

endi

x T

able

3

Seri

es N

ames

Des

crip

tion

Sour

ce

Off

icia

l exc

hang

e ra

te r

egim

eO

ffic

ial

exch

ange

rate

regi

me

isco

ded

from

1to

4as

follo

ws:

(1)

exch

ange

rate

pegg

edto

asi

ngle

curr

ency

,(2

)lim

ited

flex

ibili

ty,

(3)

man

aged

floa

ting,

and

(4)

inde

pend

ently

floa

ting.

The

var

iabl

e co

vers

30

coun

trie

s fr

om 1

993

to 1

999.

Inte

rnat

iona

l Mon

etar

y Fu

nd, E

xcha

nge

Arr

ange

men

ts a

nd

Exc

hang

e R

estr

ictio

ns

Act

ual e

xcha

nge

rate

reg

ime

(RR

)A

ctua

lexc

hang

era

tere

gim

e(R

R)

isco

ded

from

1to

15w

here

high

erva

lues

repr

esen

tm

ore

flex

ible

exch

ange

arra

ngem

ents

and

low

erva

lues

mor

efi

xed

arra

ngem

ents

.T

hecl

assi

fica

tion

isba

sed

onm

arke

t-de

term

ined

dual

orpa

ralle

lex

chan

gera

tes

asw

ell

asex

chan

gera

tes

and

infl

atio

nra

tes

from

a v

arie

ty o

f sou

rces

. The

var

iabl

e co

vers

35

coun

trie

s fr

om 1

993

to 2

000.

Rei

nhar

t and

Rog

off (

2002

)

Act

ual e

xcha

nge

rate

reg

ime

(LY

S)A

ctua

lex

chan

gera

tere

gim

e(L

YS)

isa

thre

e-w

aycl

assi

fica

tion

ofex

chan

gera

tere

gim

es.T

heva

riab

leha

sbe

entr

ansf

orm

edto

have

high

erva

lues

for

mor

efl

exib

leex

chan

gear

rang

emen

tsan

dlo

wer

valu

esm

ore

fixe

dar

rang

emen

ts.

The

clas

sifi

catio

nis

base

don

the

vola

tility

ofth

eno

min

alex

chan

ge r

ate,

the

vola

tility

of i

ts r

ate

of c

hang

e, a

nd th

e vo

latil

ity o

f the

inte

rnat

iona

l res

erve

s. T

he v

aria

ble

cove

rs 3

3 co

untr

ies

from

199

3 to

200

0.

Lev

y Y

eyat

i and

St

urze

negg

er (

2003

)

Stoc

k m

arke

t cap

italiz

atio

n (c

urre

nt U

.S. d

olla

rs)

Tot

al m

arke

t cap

italiz

atio

n in

dom

estic

sto

ck m

arke

ts.

Stan

dard

& P

oor's

(fo

rmer

IF

C)

Em

ergi

ng M

arke

ts

Dat

abas

e

Gov

ernm

ent b

onds

and

not

es

held

by

non-

resi

dent

s (c

urre

nt

U.S

. dol

lars

)

Gen

eral

gove

rnm

entb

onds

and

note

spo

rtfo

liolia

bilit

ies

atye

aren

d.T

heda

taar

epa

rtof

the

Inte

rnat

iona

lInv

estm

entP

ositi

on(I

IP)

stat

istic

sre

port

edby

the

IMF

and

repr

esen

t the

sto

ck o

f gov

ernm

ent b

onds

and

not

es h

eld

by n

on-r

esid

ents

.In

tern

atio

nal M

onet

ary

Fund

, Bal

ance

of P

aym

ents

St

atis

tics

Lon

g-te

rm d

ebt s

ecur

ities

he

ld b

y U

.S. i

nves

tors

(c

urre

nt U

.S. d

olla

rs)

U.S

.inv

esto

rs'h

oldi

ngs

offo

reig

nlo

ng-t

erm

debt

secu

ritie

sas

ofD

ecem

ber

31,1

997.

The

data

are

draw

nfr

oma

com

preh

ensi

vebe

nchm

ark

surv

eyjo

intly

und

erta

ken

by th

e U

.S. T

reas

ury

Dep

artm

ent a

nd th

e B

oard

of G

over

nors

of t

he F

eder

al R

eser

ve S

yste

m.

U.S

. Tre

asur

y D

epar

tmen

t

Tot

al d

ebt s

ecur

ities

hel

d by

fo

reig

n in

vest

ors

(cu

rren

t U

.S. d

olla

rs)

Sum

oflo

ng-

and

shor

t-te

rmde

btpo

rtfo

liolia

bilit

ies

asof

Dec

embe

r19

97.T

heda

taar

ede

rive

dfr

omcr

edito

rda

ta(d

ata

onfo

reig

nde

btse

curi

ties

held

byin

vest

ors

inea

chof

the

repo

rtin

gco

untr

ies)

.T

heda

taar

edr

awn

from

asu

rvey

ofpo

rtfo

lioin

vest

men

tas

sets

whe

re29

econ

omie

spa

rtic

ipat

ed.

Inte

rnat

iona

l Mon

etar

y Fu

nd, C

oord

inat

ed P

ortf

olio

In

vest

men

t Sur

vey

(CPI

S)

GD

P pe

r ca

pita

Gro

ss d

omes

tic p

rodu

ct (

GD

P) d

ivid

ed b

y m

id-y

ear

popu

latio

n.T

he W

orld

Ban

k, W

orld

D

evel

opm

ent I

ndic

ator

s

Eng

lish

lega

l ori

gin

Dum

my

iden

tifiy

ing

the

lega

lori

gin

ofth

eC

ompa

nyL

awor

Com

mer

cial

Cod

eof

each

coun

try.

The

rear

efi

vepo

ssib

leor

igin

s:(1

)E

nglis

hC

omm

onL

aw;

(2)

Fren

chC

omm

erci

alC

ode;

(3)

Ger

man

Com

mer

cial

Cod

e;(4

)Sc

andi

navi

anC

omm

erci

alC

ode;

and

(5)

Soci

alis

t/Com

mun

ist

Law

s.T

hedu

mm

y eq

uals

one

if th

e co

untr

y's

Com

pany

Law

ori

gina

tes

from

Eng

lish

Com

mon

Law

and

zer

o ot

herw

ise.

La

Port

a et

al.

(199

9)

Cap

ital a

ccou

nt o

pene

ssIn

dex

onca

pita

lac

coun

top

enne

ssba

sed

onth

efo

urbi

nary

dum

my

vari

able

sre

port

edin

the

IMF’

sA

nnua

lRep

ort

onE

xcha

nge

Arr

ange

men

tsan

dE

xcha

nge

Res

tric

tions

:(1

)pr

esen

ceof

mul

tiple

exch

ange

rate

s,(2

)re

stri

ctio

nson

curr

ent

acco

unt

tran

sact

ions

,(3

)re

stri

ctio

nson

capi

tal

acco

unt

tran

sact

ions

,and

(4)

requ

irem

ento

fth

esu

rren

der

ofex

port

proc

eeds

.In

orde

rto

focu

son

the

effe

ctof

fina

ncia

lope

nnes

s–

rath

erth

anco

ntro

ls–

the

vari

able

sar

eeq

ualt

oon

ew

hen

the

capi

tala

ccou

ntre

stri

ctio

nsar

eno

n-ex

iste

nt.F

orco

ntro

lson

capi

talt

rans

actio

nsth

ein

dex

cons

ider

sth

esh

are

ofa

five

-yea

rw

indo

wth

atca

pita

lco

ntro

lsw

ere

not

inef

fect

(3b)

.T

heca

pita

lac

coun

top

enes

sin

dex

isca

lcul

ated

asth

efi

rst

stan

dard

ized

prin

cipa

lco

mpo

nent

of(1

),(2

),(3

b),

and

(4).

The

inde

xta

kes

onhi

gher

valu

esth

em

ore

open

the

coun

try

isto

cros

s-bo

rder

capi

tal

tran

sact

ions

.B

yco

nstr

uctio

n, th

e in

dex

has

a m

ean

of z

ero.

Chi

nn a

nd I

to (

2005

)

Infl

atio

n (t

hree

-yea

r av

erag

e)T

hree

-yea

r m

ovin

g av

erag

e of

ann

ual i

nfla

tion

rate

, as

mea

sure

d by

the

cons

umer

pri

ce in

dex.

The

Wor

ld B

ank,

Wor

ld

Dev

elop

men

t Ind

icat

ors